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Статті в журналах з теми "Relation extractor"
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Yuan, Yujin, Liyuan Liu, Siliang Tang, Zhongfei Zhang, Yueting Zhuang, Shiliang Pu, Fei Wu, and Xiang Ren. "Cross-Relation Cross-Bag Attention for Distantly-Supervised Relation Extraction." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 419–26. http://dx.doi.org/10.1609/aaai.v33i01.3301419.
Повний текст джерелаАнотація:
Distant supervision leverages knowledge bases to automatically label instances, thus allowing us to train relation extractor without human annotations. However, the generated training data typically contain massive noise, and may result in poor performances with the vanilla supervised learning. In this paper, we propose to conduct multi-instance learning with a novel Cross-relation Cross-bag Selective Attention (C2SA), which leads to noise-robust training for distant supervised relation extractor. Specifically, we employ the sentence-level selective attention to reduce the effect of noisy or mismatched sentences, while the correlation among relations were captured to improve the quality of attention weights. Moreover, instead of treating all entity-pairs equally, we try to pay more attention to entity-pairs with a higher quality. Similarly, we adopt the selective attention mechanism to achieve this goal. Experiments with two types of relation extractor demonstrate the superiority of the proposed approach over the state-of-the-art, while further ablation studies verify our intuitions and demonstrate the effectiveness of our proposed two techniques.
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Kim, Kuekyeng, Yuna Hur, Gyeongmin Kim, and Heuiseok Lim. "GREG: A Global Level Relation Extraction with Knowledge Graph Embedding." Applied Sciences 10, no. 3 (February 10, 2020): 1181. http://dx.doi.org/10.3390/app10031181.
Повний текст джерелаАнотація:
In an age overflowing with information, the task of converting unstructured data into structured data are a vital task of great need. Currently, most relation extraction modules are more focused on the extraction of local mention-level relations—usually from short volumes of text. However, in most cases, the most vital and important relations are those that are described in length and detail. In this research, we propose GREG: A Global level Relation Extractor model using knowledge graph embeddings for document-level inputs. The model uses vector representations of mention-level ‘local’ relation’s to construct knowledge graphs that can represent the input document. The knowledge graph is then used to predict global level relations from documents or large bodies of text. The proposed model is largely divided into two modules which are synchronized during their training. Thus, each of the model’s modules is designed to deal with local relations and global relations separately. This allows the model to avoid the problem of struggling against loss of information due to too much information crunched into smaller sized representations when attempting global level relation extraction. Through evaluation, we have shown that the proposed model yields high performances in both predicting global level relations and local level relations consistently.
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Oliveira Neto, Waldemar de, Antonio Saraiva Muniz, Maria Anita Gonçalves da Silva, Cesar de Castro, and Clovis Manuel Borkert. "Boron extraction and vertical mobility in Paraná State oxisol, Brazil." Revista Brasileira de Ciência do Solo 33, no. 5 (October 2009): 1259–67. http://dx.doi.org/10.1590/s0100-06832009000500019.
Повний текст джерелаАнотація:
The deficiency or excess of micronutrients has been determined by analyses of soil and plant tissue. In Brazil, the lack of studies that would define and standardize extraction and determination methods, as well as lack of correlation and calibration studies, makes it difficult to establish limits of concentration classes for analysis interpretation and fertilizer recommendations for crops. A specific extractor for soil analysis is sometimes chosen due to the ease of use in the laboratory and not in view of its efficiency in determining a bioavailable nutrient. The objectives of this study were to: (a) evaluate B concentrations in the soil as related to the fertilizer rate, soil depth and extractor; (b) verify the nutrient movement in the soil profile; (c) evaluate efficiency of Hot Water, Mehlich-1 and Mehlich-3 as available B extractors, using sunflower as test plant. The experimental design consisted of complete randomized blocks with four replications and treatments of five B rates (0, 2, 4, 6, and 8 kg ha-1) applied to the soil surface and evaluated at six depths (0-0.05, 0.05-0.10, 0.10-0.15, 0.15-0.20, 0.20-0.30, and 0.30-0.40 m). Boron concentrations in the soil extracted by Hot Water, Mehlich-1 and Mehlich-3 extractors increased linearly in relation to B rates at all depths evaluated, indicating B mobility in the profile. The extractors had different B extraction capacities, but were all efficient to evaluate bioavailability of the nutrient to sunflower. Mehlich-1 and Mehlich-3 can therefore be used to analyze B as well as Hot Water.
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Zhang, Congle, Stephen Soderland, and Daniel S. Weld. "Exploiting Parallel News Streams for Unsupervised Event Extraction." Transactions of the Association for Computational Linguistics 3 (December 2015): 117–29. http://dx.doi.org/10.1162/tacl_a_00127.
Повний текст джерелаАнотація:
Most approaches to relation extraction, the task of extracting ground facts from natural language text, are based on machine learning and thus starved by scarce training data. Manual annotation is too expensive to scale to a comprehensive set of relations. Distant supervision, which automatically creates training data, only works with relations that already populate a knowledge base (KB). Unfortunately, KBs such as FreeBase rarely cover event relations ( e.g. “person travels to location”). Thus, the problem of extracting a wide range of events — e.g., from news streams — is an important, open challenge. This paper introduces NewsSpike-RE, a novel, unsupervised algorithm that discovers event relations and then learns to extract them. NewsSpike-RE uses a novel probabilistic graphical model to cluster sentences describing similar events from parallel news streams. These clusters then comprise training data for the extractor. Our evaluation shows that NewsSpike-RE generates high quality training sentences and learns extractors that perform much better than rival approaches, more than doubling the area under a precision-recall curve compared to Universal Schemas.
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Li, Bo, Jiyu Wei, Yang Liu, Yuze Chen, Xi Fang, and Bin Jiang. "Few-Shot Relation Extraction on Ancient Chinese Documents." Applied Sciences 11, no. 24 (December 17, 2021): 12060. http://dx.doi.org/10.3390/app112412060.
Повний текст джерелаАнотація:
Traditional humanity scholars’ inefficient method of utilizing numerous unstructured data has hampered studies on ancient Chinese writings for several years. In this work, we aim to develop a relation extractor for ancient Chinese documents to automatically extract the relations by using unstructured data. To achieve this goal, we proposed a tiny ancient Chinese document relation classification (TinyACD-RC) dataset annotated by historians and contains 32 types of general relations in ShihChi (a famous Chinese history book). We also explored several methods and proposed a novel model that works well on sufficient and insufficient data scenarios, the proposed sentence encoder can simultaneously capture local and global features for a certain period. The paired attention network enhances and extracts relations between support and query instances. Experimental results show that our model achieved promising performance with scarce corpus. We also examined our model on the FewRel dataset and found that outperformed the state-of-the-art no pretraining-based models by 2.27%.
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Toma, Claudia Crina, Teresa Casacchia, Claudia D`ippolito, and Giancarlo Statti. "Ficus carica SSP Dottato Buds by Intercropping Different Species: Metabolites, Antioxidant Activity and Endogenous Plant Hormones (IAA, ABA)." Revista de Chimie 68, no. 7 (August 15, 2017): 1628–31. http://dx.doi.org/10.37358/rc.17.7.5731.
Повний текст джерелаАнотація:
Ficus carica is one of the most common tree crops in the Mediterranean basin. Its ethnobotanic use has been extensively studied to evaluate its biological activity in relation to the presence of specific secondary metabolites. In this paper, the extract of the gemstones of the ficus carica ssp dottato di Cosenza was studied with respect to different vegetation habitats (intercrops) and two different extraction techniques. Buds, in fact, are used in gemotherapy as macerated glycerides obtained by long extraction processes (21 Days).The use of a Dynamic extractor (Naviglio� Extractor) has allowed not only to reduce the extraction time (10 h) but to obtain a qualitatively and quantitatively enriched extract withactive ingredients to which the specific biological activity is reported. In fact, the total polyphenolic and total flavonoid components were determined, of which Quercetin-3O-Glucoside and 3-O-Rhamnoside were dosed, and the resulting anti-oxidant activity. IAA and ABA have also been quantified.
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Marcheggiani, Diego, and Ivan Titov. "Discrete-State Variational Autoencoders for Joint Discovery and Factorization of Relations." Transactions of the Association for Computational Linguistics 4 (December 2016): 231–44. http://dx.doi.org/10.1162/tacl_a_00095.
Повний текст джерелаАнотація:
We present a method for unsupervised open-domain relation discovery. In contrast to previous (mostly generative and agglomerative clustering) approaches, our model relies on rich contextual features and makes minimal independence assumptions. The model is composed of two parts: a feature-rich relation extractor, which predicts a semantic relation between two entities, and a factorization model, which reconstructs arguments (i.e., the entities) relying on the predicted relation. The two components are estimated jointly so as to minimize errors in recovering arguments. We study factorization models inspired by previous work in relation factorization and selectional preference modeling. Our models substantially outperform the generative and agglomerative-clustering counterparts and achieve state-of-the-art performance.
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Dowling, AJ, and CJ Howitt. "Effects of extraction technique on concentrations of soluble salts in soil saturation extracts." Soil Research 25, no. 2 (1987): 137. http://dx.doi.org/10.1071/sr9870137.
Повний текст джерелаАнотація:
Solution yield and saturation extract salinity for a range of south-east Queensland soils are described in relation to solution extraction by leaching, over a range of extraction times, and by centrifuging. Yield, pH, [Ca] and [HCO3] were affected by extraction technique. In leached extracts, compared with centrifuged extracts, solution pH was more variable and [HCO3] and [Ca] were higher. Leaching overnight consistently produced solution yields in excess of 20 g 100g-1 added water to saturation. Variations in these attributes reflect differences between the two extraction techniques which can be explained in terms of variable levels of CO2 in the solution collection assembly with air entry during extraction. Centrifuging minimised air entry and, hence, the gadliquid ratio in the extractor. The CO2 mediated changes are thus less for centrifuged than leached extracts. Centrifuging, as an extraction technique, therefore, has more relevance than leaching if specific mineralogic controls on solution composition are being determined.
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Wu, Ming-Jui, Wei-Ling Chen, Chung-Dann Kan, Fan-Ming Yu, Su-Chin Wang, Hsiu-Hui Lin, and Chia-Hung Lin. "Dysfunction Screening in Experimental Arteriovenous Grafts for Hemodialysis Using Fractional-Order Extractor and Color Relation Analysis." Cardiovascular Engineering and Technology 6, no. 4 (August 4, 2015): 463–73. http://dx.doi.org/10.1007/s13239-015-0239-5.
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OLALERE, OLUSEGUN ABAYOMI. "COMPARATIVE STUDY OF PULSED MICROWAVE AND HYDRODISTILLATION EXTRACTION OF PIPERINE OIL FROM BLACK PEPPER." IIUM Engineering Journal 18, no. 2 (December 1, 2017): 87–93. http://dx.doi.org/10.31436/iiumej.v18i2.802.
Повний текст джерелаАнотація:
Black pepper is a tropical crop with an extensive medicinal potential in alternative medicine and nutraceutical applications. The pungent bioactive piperine is responsible for this functions and its efficacy requires an efficient extraction technologies for optimal isolation. There is therefore a need to determine the best factor settings that will optimize the relative efficiency of the extraction system with minimal variability. The best factor settings was achieved using the L9 Taguchi parametric orthogonal design. The extraction parameters considered under this study were extraction time, irradiation power level, particle size and molar ratio. An optimal extraction condition was therefore achieved at 90 min extraction time, 350 W microwave power, 0.105 mm particle size and 10 mL/g molar ratio. The signal-to-noise ratio (SNR) otherwise known as response optimizer is an ideal metric in the determination of this optimum condition. The performance evaluation of reflux microwave extractor in relation to that of the hydrodistillation system placed the optimal efficiency and signal-to-noise ratio at 155.72% and 43.8469, respectively. The higher optimal efficiency obtained indicated that the microwave reflux extraction is better and more efficient than the conventional hydrodistillation techniques.
Дисертації з теми "Relation extractor"
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Філоненко, О. В., Олена Петрівна Черних та Олександр Миколайович Шеін. "Фільтрування інтернет спаму за допомогою обробки природної мови". Thesis, Національний технічний університет "Харківський політехнічний інститут", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/43684.
Повний текст джерела
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Scheible, Silke. "Computational treatment of superlatives." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4153.
Повний текст джерелаАнотація:
The use of gradable adjectives and adverbs represents an important means of expressing comparison in English. The grammatical forms of comparatives and superlatives are used to express explicit orderings between objects with respect to the degree to which they possess some gradable property. While comparatives are commonly used to compare two entities (e.g., “The blue whale is larger than an African elephant”), superlatives such as “The blue whale is the largest mammal” are used to express a comparison between a target entity (here, the blue whale) and its comparison set (the set of mammals), with the target ranked higher or lower on a scale of comparison than members of the comparison set. Superlatives thus highlight the uniqueness of the target with respect to its comparison set. Although superlatives are frequently found in natural language, with the exception of recent work by (Bos and Nissim, 2006) and (Jindal and Liu, 2006b), they have not yet been investigated within a computational framework. And within the framework of theoretical linguistics, studies of superlatives have mainly focused on semantic properties that may only rarely occur in natural language (Szabolsci (1986), Heim (1999)). My PhD research aims to pave the way for a comprehensive computational treatment of superlatives. The initial question I am addressing is that of automatically extracting useful information about the target entity, its comparison set and their relationship from superlative constructions. One of the central claims of the thesis is that no unified computational treatment of superlatives is possible because of their great semantic complexity and the variety of syntactic structures in which they occur. I propose a classification of superlative surface forms, and initially focus on so-called “ISA superlatives”, which make explicit the IS-A relation that holds between target and comparison set. They are suitable for a computational approach because both their target and comparison set are usually explicitly realised in the text. I also aim to show that the findings of this thesis are of potential benefit for NLP applications such as Question Answering, Natural Language Generation, Ontology Learning, and Sentiment Analysis/Opinion Mining. In particular, I investigate the use of the “Superlative Relation Extractor“ implemented in this project in the area of Sentiment Analysis/Opinion Mining, and claim that a superlative analysis of the sort presented in this thesis, when applied to product evaluations and recommendations, can provide just the kind of information that Opinion Mining aims to identify.
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Hachey, Benjamin. "Towards generic relation extraction." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3978.
Повний текст джерелаАнотація:
A vast amount of usable electronic data is in the form of unstructured text. The relation extraction task aims to identify useful information in text (e.g., PersonW works for OrganisationX, GeneY encodes ProteinZ) and recode it in a format such as a relational database that can be more effectively used for querying and automated reasoning. However, adapting conventional relation extraction systems to new domains or tasks requires significant effort from annotators and developers. Furthermore, previous adaptation approaches based on bootstrapping start from example instances of the target relations, thus requiring that the correct relation type schema be known in advance. Generic relation extraction (GRE) addresses the adaptation problem by applying generic techniques that achieve comparable accuracy when transferred, without modification of model parameters, across domains and tasks. Previous work on GRE has relied extensively on various lexical and shallow syntactic indicators. I present new state-of-the-art models for GRE that incorporate governordependency information. I also introduce a dimensionality reduction step into the GRE relation characterisation sub-task, which serves to capture latent semantic information and leads to significant improvements over an unreduced model. Comparison of dimensionality reduction techniques suggests that latent Dirichlet allocation (LDA) – a probabilistic generative approach – successfully incorporates a larger and more interdependent feature set than a model based on singular value decomposition (SVD) and performs as well as or better than SVD on all experimental settings. Finally, I will introduce multi-document summarisation as an extrinsic test bed for GRE and present results which demonstrate that the relative performance of GRE models is consistent across tasks and that the GRE-based representation leads to significant improvements over a standard baseline from the literature. Taken together, the experimental results 1) show that GRE can be improved using dependency parsing and dimensionality reduction, 2) demonstrate the utility of GRE for the content selection step of extractive summarisation and 3) validate the GRE claim of modification-free adaptation for the first time with respect to both domain and task. This thesis also introduces data sets derived from publicly available corpora for the purpose of rigorous intrinsic evaluation in the news and biomedical domains.
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NUNES, THIAGO RIBEIRO. "BUILDING RELATION EXTRACTORS THROUGH DISTANT SUPERVISION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=21588@1.
Повний текст джерелаАнотація:
PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIROCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Um problema conhecido no processo de construção de extratores de relações semânticas supervisionados em textos em linguagem natural é a disponibilidade de uma quantidade suficiente de exemplos positivos para um conjunto amplo de relações-alvo. Este trabalho apresenta uma abordagem supervisionada a distância para construção de extratores de relações a um baixo custo combinando duas das maiores fontes de informação estruturada e não estruturada disponíveis na Web, o DBpedia e a Wikipedia. O método implementado mapeia relações da ontologia do DBpedia de volta para os textos da Wikipedia para montar um conjunto amplo de exemplos contendo mais de 100.000 sentenças descrevendo mais de 90 relações do DBpedia para os idiomas Inglês e Português. Inicialmente, são extraídas sentenças dos artigos da Wikipedia candidatas a expressar relações do DBpedia. Após isso, esses dados são pré-processados e normalizados através da filtragem de sentenças irrelevantes. Finalmente, extraem-se características dos exemplos para treinamento e avaliação de extratores de relações utilizando SVM. Os experimentos realizados nos idiomas Inglês e Português, através de linhas de base, mostram as melhorias alcançadas quando combinados diferentes tipos de características léxicas, sintáticas e semânticas. Para o idioma Inglês, o extrator construído foi treinado em um corpus constituído de 90 relações com 42.471 exemplos de treinamento, atingindo 81.08 por cento de medida F1 em um conjunto de testes contendo 28.773 instâncias. Para Português, o extrator foi treinado em um corpus de 50 relações com 200 exemplos por relação, resultando em um valor de 81.91 por cento de medida F1 em um conjunto de testes contendo 18.333 instâncias. Um processo de Extração de Relações (ER) é constituído de várias etapas, que vão desde o pré-processamento dos textos até o treinamento e a avaliação de detectores de relações supervisionados. Cada etapa pode admitir a implementação de uma ou várias técnicas distintas. Portanto, além da abordagem, este trabalho apresenta, também, detalhes da arquitetura de um framework para apoiar a implementação e a realização de experimentos em um processo de ER.
A well known drawback in building machine learning semantic relation detectors for natural language is the availability of a large number of qualified training instances for the target relations. This work presents an automatic approach to build multilingual semantic relation detectors through distant supervision combining the two largest resources of structured and unstructured content available on the Web, the DBpedia and the Wikipedia resources. We map the DBpedia ontology back to the Wikipedia to extract more than 100.000 training instances for more than 90 DBpedia relations for English and Portuguese without human intervention. First, we mine the Wikipedia articles to find candidate instances for relations described at DBpedia ontology. Second, we preprocess and normalize the data filtering out irrelevant instances. Finally, we use the normalized data to construct SVM detectors. The experiments performed on the English and Portuguese baselines shows that the lexical and syntactic features extracted from Wikipedia texts combined with the semantic features extracted from DBpedia can significantly improve the performance of relation detectors. For English language, the SVM detector was trained in a corpus formed by 90 DBpedia relations and 42.471 training instances, achieving 81.08 per cent of F-Measure when applied to a test set formed by 28.773 instances. The Portuguese detector was trained with 50 DBpedia relations and 200 examples by relation, being evaluated in 81.91 per cent of F-Measure in a test set containing 18.333 instances. A Relation Extraction (RE) process has many distinct steps that usually begins with text pre-processing and finish with the training and the evaluation of relation detectors. Therefore, this works not only presents an RE approach but also an architecture of a framework that supports the implementation and the experiments of a RE process.
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Minard, Anne-Lyse. "Extraction de relations en domaine de spécialité." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00777749.
Повний текст джерелаАнотація:
La quantité d'information disponible dans le domaine biomédical ne cesse d'augmenter. Pour que cette information soit facilement utilisable par les experts d'un domaine, il est nécessaire de l'extraire et de la structurer. Pour avoir des données structurées, il convient de détecter les relations existantes entre les entités dans les textes. Nos recherches se sont focalisées sur la question de l'extraction de relations complexes représentant des résultats expérimentaux, et sur la détection et la catégorisation de relations binaires entre des entités biomédicales. Nous nous sommes intéressée aux résultats expérimentaux présentés dans les articles scientifiques. Nous appelons résultat expérimental, un résultat quantitatif obtenu suite à une expérience et mis en relation avec les informations permettant de décrire cette expérience. Ces résultats sont importants pour les experts en biologie, par exemple pour faire de la modélisation. Dans le domaine de la physiologie rénale, une base de données a été créée pour centraliser ces résultats d'expérimentation, mais l'alimentation de la base est manuelle et de ce fait longue. Nous proposons une solution pour extraire automatiquement des articles scientifiques les connaissances pertinentes pour la base de données, c'est-à-dire des résultats expérimentaux que nous représentons par une relation n-aire. La méthode procède en deux étapes : extraction automatique des documents et proposition de celles-ci pour validation ou modification par l'expert via une interface. Nous avons également proposé une méthode à base d'apprentissage automatique pour l'extraction et la classification de relations binaires en domaine de spécialité. Nous nous sommes intéressée aux caractéristiques et variétés d'expressions des relations, et à la prise en compte de ces caractéristiques dans un système à base d'apprentissage. Nous avons étudié la prise en compte de la structure syntaxique de la phrase et la simplification de phrases dirigée pour la tâche d'extraction de relations. Nous avons en particulier développé une méthode de simplification à base d'apprentissage automatique, qui utilise en cascade plusieurs classifieurs.
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Augenstein, Isabelle. "Web relation extraction with distant supervision." Thesis, University of Sheffield, 2016. http://etheses.whiterose.ac.uk/13247/.
Повний текст джерелаАнотація:
Being able to find relevant information about prominent entities quickly is the main reason to use a search engine. However, with large quantities of information on the World Wide Web, real time search over billions of Web pages can waste resources and the end user’s time. One of the solutions to this is to store the answer to frequently asked general knowledge queries, such as the albums released by a musical artist, in a more accessible format, a knowledge base. Knowledge bases can be created and maintained automatically by using information extraction methods, particularly methods to extract relations between proper names (named entities). A group of approaches for this that has become popular in recent years are distantly supervised approaches as they allow to train relation extractors without text-bound annotation, using instead known relations from a knowledge base to heuristically align them with a large textual corpus from an appropriate domain. This thesis focuses on researching distant supervision for the Web domain. A new setting for creating training and testing data for distant supervision from the Web with entity-specific search queries is introduced and the resulting corpus is published. Methods to recognise noisy training examples as well as methods to combine extractions based on statistics derived from the background knowledge base are researched. Using co-reference resolution methods to extract relations from sentences which do not contain a direct mention of the subject of the relation is also investigated. One bottleneck for distant supervision for Web data is identified to be named entity recognition and classification (NERC), since relation extraction methods rely on it for identifying relation arguments. Typically, existing pre-trained tools are used, which fail in diverse genres with non-standard language, such as the Web genre. The thesis explores what can cause NERC methods to fail in diverse genres and quantifies different reasons for NERC failure. Finally, a novel method for NERC for relation extraction is proposed based on the idea of jointly training the named entity classifier and the relation extractor with imitation learning to reduce the reliance on external NERC tools. This thesis improves the state of the art in distant supervision for knowledge base population, and sheds light on and proposes solutions for issues arising for information extraction for not traditionally studied domains.
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Jean-Louis, Ludovic. "Approches supervisées et faiblement supervisées pour l’extraction d’événements et le peuplement de bases de connaissances." Thesis, Paris 11, 2011. http://www.theses.fr/2011PA112288/document.
Повний текст джерелаАнотація:
La plus grande partie des informations disponibles librement sur le Web se présentent sous une forme textuelle, c'est-à-dire non-structurée. Dans un contexte comme celui de la veille, il est très utile de pouvoir présenter les informations présentes dans les textes sous une forme structurée en se focalisant sur celles jugées pertinentes vis-à-vis du domaine d'intérêt considéré. Néanmoins, lorsque l'on souhaite traiter ces informations de façon systématique, les méthodes manuelles ne sont pas envisageables du fait du volume important des données à considérer.L'extraction d'information s'inscrit dans la perspective de l'automatisation de ce type de tâches en identifiant dans des textes les informations concernant des faits (ou événements) afin de les stocker dans des structures de données préalablement définies. Ces structures, appelées templates (ou formulaires), agrègent les informations caractéristiques d'un événement ou d'un domaine d'intérêt représentées sous la forme d'entités nommées (nom de lieux, etc.).Dans ce contexte, le travail de thèse que nous avons mené s'attache à deux grandes problématiques : l'identification des informations liées à un événement lorsque ces informations sont dispersées à une échelle textuelle en présence de plusieurs occurrences d'événements de même type;la réduction de la dépendance vis-à-vis de corpus annotés pour la mise en œuvre d'un système d'extraction d'information.Concernant la première problématique, nous avons proposé une démarche originale reposant sur deux étapes. La première consiste en une segmentation événementielle identifiant dans un document les zones de texte faisant référence à un même type d'événements, en s'appuyant sur des informations de nature temporelle. Cette segmentation détermine ainsi les zones sur lesquelles le processus d'extraction doit se focaliser. La seconde étape sélectionne à l'intérieur des segments identifiés comme pertinents les entités associées aux événements. Elle conjugue pour ce faire une extraction de relations entre entités à un niveau local et un processus de fusion global aboutissant à un graphe d'entités. Un processus de désambiguïsation est finalement appliqué à ce graphe pour identifier l'entité occupant un rôle donné vis-à-vis d'un événement lorsque plusieurs sont possibles.La seconde problématique est abordée dans un contexte de peuplement de bases de connaissances à partir de larges ensembles de documents (plusieurs millions de documents) en considérant un grand nombre (une quarantaine) de types de relations binaires entre entités nommées. Compte tenu de l'effort représenté par l'annotation d'un corpus pour un type de relations donné et du nombre de types de relations considérés, l'objectif est ici de s'affranchir le plus possible du recours à une telle annotation tout en conservant une approche par apprentissage. Cet objectif est réalisé par le biais d'une approche dite de supervision distante prenant comme point de départ des exemples de relations issus d'une base de connaissances et opérant une annotation non supervisée de corpus en fonction de ces relations afin de constituer un ensemble de relations annotées destinées à la construction d'un modèle par apprentissage. Cette approche a été évaluée à large échelle sur les données de la campagne TAC-KBP 2010The major part of the information available on the web is provided in textual form, i.e. in unstructured form. In a context such as technology watch, it is useful to present the information extracted from a text in a structured form, reporting only the pieces of information that are relevant to the considered field of interest. Such processing cannot be performed manually at large scale, given the large amount of data available. The automated processing of this task falls within the Information extraction (IE) domain.The purpose of IE is to identify, within documents, pieces of information related to facts (or events) in order to store this information in predefined data structures. These structures, called templates, aggregate fact properties - often represented by named entities - concerning an event or an area of interest.In this context, the research performed in this thesis addresses two problems:identifying information related to a specific event, when the information is scattered across a text and several events of the same type are mentioned in the text;reducing the dependency to annotated corpus for the implementation of an Information Extraction system.Concerning the first problem, we propose an original approach that relies on two steps. The first step operates an event-based text segmentation, which identifies within a document the text segments on which the IE process shall focus to look for the entities associated with a given event. The second step focuses on template filling and aims at selecting, within the segments identified as relevant by the event-based segmentation, the entities that should be used as fillers, using a graph-based method. This method is based on a local extraction of relations between entities, that are merged in a relation graph. A disambiguation step is then performed on the graph to identify the best candidates to fill the information template.The second problem is treated in the context of knowledge base (KB) population, using a large collection of texts (several millions) from which the information is extracted. This extraction also concerns a large number of relation types (more than 40), which makes the manual annotation of the collection too expensive. We propose, in this context, a distant supervision approach in order to use learning techniques for this extraction, without the need of a fully annotated corpus. This distant supervision approach uses a set of relations from an existing KB to perform an unsupervised annotation of a collection, from which we learn a model for relation extraction. This approach has been evaluated at a large scale on the data from the TAC-KBP 2010 evaluation campaign
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Afzal, Naveed. "Unsupervised relation extraction for e-learning applications." Thesis, University of Wolverhampton, 2011. http://hdl.handle.net/2436/299064.
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In this modern era many educational institutes and business organisations are adopting the e-Learning approach as it provides an effective method for educating and testing their students and staff. The continuous development in the area of information technology and increasing use of the internet has resulted in a huge global market and rapid growth for e-Learning. Multiple Choice Tests (MCTs) are a popular form of assessment and are quite frequently used by many e-Learning applications as they are well adapted to assessing factual, conceptual and procedural information. In this thesis, we present an alternative to the lengthy and time-consuming activity of developing MCTs by proposing a Natural Language Processing (NLP) based approach that relies on semantic relations extracted using Information Extraction to automatically generate MCTs. Information Extraction (IE) is an NLP field used to recognise the most important entities present in a text, and the relations between those concepts, regardless of their surface realisations. In IE, text is processed at a semantic level that allows the partial representation of the meaning of a sentence to be produced. IE has two major subtasks: Named Entity Recognition (NER) and Relation Extraction (RE). In this work, we present two unsupervised RE approaches (surface-based and dependency-based). The aim of both approaches is to identify the most important semantic relations in a document without assigning explicit labels to them in order to ensure broad coverage, unrestricted to predefined types of relations. In the surface-based approach, we examined different surface pattern types, each implementing different assumptions about the linguistic expression of semantic relations between named entities while in the dependency-based approach we explored how dependency relations based on dependency trees can be helpful in extracting relations between named entities. Our findings indicate that the presented approaches are capable of achieving high precision rates. Our experiments make use of traditional, manually compiled corpora along with similar corpora automatically collected from the Web. We found that an automatically collected web corpus is still unable to ensure the same level of topic relevance as attained in manually compiled traditional corpora. Comparison between the surface-based and the dependency-based approaches revealed that the dependency-based approach performs better. Our research enabled us to automatically generate questions regarding the important concepts present in a domain by relying on unsupervised relation extraction approaches as extracted semantic relations allow us to identify key information in a sentence. The extracted patterns (semantic relations) are then automatically transformed into questions. In the surface-based approach, questions are automatically generated from sentences matched by the extracted surface-based semantic pattern which relies on a certain set of rules. Conversely, in the dependency-based approach questions are automatically generated by traversing the dependency tree of extracted sentence matched by the dependency-based semantic patterns. The MCQ systems produced from these surface-based and dependency-based semantic patterns were extrinsically evaluated by two domain experts in terms of questions and distractors readability, usefulness of semantic relations, relevance, acceptability of questions and distractors and overall MCQ usability. The evaluation results revealed that the MCQ system based on dependency-based semantic relations performed better than the surface-based one. A major outcome of this work is an integrated system for MCQ generation that has been evaluated by potential end users.
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Loper, Edward (Edward Daniel) 1977. "Applying semantic relation extraction to information retrieval." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86521.
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Imani, Mahsa. "Evaluating open relation extraction over conversational texts." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/45978.
Повний текст джерелаАнотація:
In this thesis, for the first time the performance of Open IE systems on conversational data has been studied. Due to lack of test datasets in this domain, a method for creating the test dataset covering a wide range of conversational data has been proposed. Conversational text is more complex and challenging for relation extraction because of its cryptic content and ungrammatical colloquial language. As a consequence text simplification has been used as a remedy to empower Open IE tools for relation extraction. Experimental results show that text simplification helps OLLIE, a state of the art for relation extraction, find new relations, extract more accurate relations and assign higher confidence scores to correct relations and lower confidence scores to incorrect relations for most datasets. Results also show some conversational modalities such as emails and blogs are easier for relation extraction task while people reviews on products is the most difficult modality.
Книги з теми "Relation extractor"
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Hudson, R. A. Extraction and grammatical relations. London: The author, 1987.
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Xu, Fei-Yu. Bootstrapping relation extraction from semantic seeds. Saarbrücken: German Research Center for Artificial Intelligence, 2008.
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Petrucci, Alessandra, and Rosanna Verde, eds. SIS 2017. Statistics and Data Science: new challenges, new generations. Florence: Firenze University Press, 2017. http://dx.doi.org/10.36253/978-88-6453-521-0.
Повний текст джерелаАнотація:
The 2017 SIS Conference aims to highlight the crucial role of the Statistics in Data Science. In this new domain of ‘meaning’ extracted from the data, the increasing amount of produced and available data in databases, nowadays, has brought new challenges. That involves different fields of statistics, machine learning, information and computer science, optimization, pattern recognition. These afford together a considerable contribute in the analysis of ‘Big data’, open data, relational and complex data, structured and no-structured. The interest is to collect the contributes which provide from the different domains of Statistics, in the high dimensional data quality validation, sampling extraction, dimensional reduction, pattern selection, data modelling, testing hypotheses and confirming conclusions drawn from the data.
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Rietbergen, Simon. Conservation concerns relating to the diversification of species extracted for timber. London: The Institute, 1991.
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Higginson, Francis. Extracts from Francis Higginson: A brief relation of the irreligion of the northern Quakers. Oxford: E. Warren, 1999.
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Hoxha, Enver. The superpowers, 1959-1984: Extracts from the political diary. Tiranë: 8 Nëntori, 1986.
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Parliament, Great Britain. Canada: Copies or extracts of correspondence relative to the affairs of Canada. [London: HMSO, 2001.
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Chikyū Ondanka Mondai ni Kansuru Chōsakai Japan. Kokkai. Sangiin. Kokusai. Research report on international affairs and global warming issues: Interim report (extracts). Tokyo: Research Committee on International Affairs and Global Warming Issues, House of Councillors, 2008.
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Barlow, Alfred E. Report on the origin, geological relations and composition of the nickel and copper deposits of the Sudbury mining district, Ontario, Canada. Ottawa: S.E. Dawson, 1997.
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Parliament, Great Britain. Copies or extracts of correspondence relative to the reunion of the provinces of Upper and Lower Canada. [London: HMSO, 2001.
Знайти повний текст джерелаЧастини книг з теми "Relation extractor"
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Rossiello, Gaetano, Alfio Gliozzo, Nicolas Fauceglia, and Giovanni Semeraro. "Latent Relational Model for Relation Extraction." In The Semantic Web, 283–97. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21348-0_19.
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Denecke, Kerstin. "Relation Extraction." In Health Web Science, 75–81. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20582-3_9.
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Castelli, Vittorio, and Imed Zitouni. "Relation Extraction." In Natural Language Processing of Semitic Languages, 279–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45358-8_9.
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Soni, Ameet, Dileep Viswanathan, Jude Shavlik, and Sriraam Natarajan. "Learning Relational Dependency Networks for Relation Extraction." In Inductive Logic Programming, 81–93. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63342-8_7.
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Rendle, Steffen, Christine Preisach, and Lars Schmidt-Thieme. "Learning to Extract Relations for Relational Classification." In Advances in Knowledge Discovery and Data Mining, 1062–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01307-2_114.
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Sowa, John F. "Relating Templates to Language and Logic." In Information Extraction, 76–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48089-7_5.
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Kordjamshidi, Parisa, Paolo Frasconi, Martijn Van Otterlo, Marie-Francine Moens, and Luc De Raedt. "Relational Learning for Spatial Relation Extraction from Natural Language." In Inductive Logic Programming, 204–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31951-8_20.
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Elsahar, Hady, Elena Demidova, Simon Gottschalk, Christophe Gravier, and Frederique Laforest. "Unsupervised Open Relation Extraction." In Lecture Notes in Computer Science, 12–16. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70407-4_3.
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Barrière, Caroline. "Pattern-Based Relation Extraction." In Natural Language Understanding in a Semantic Web Context, 205–29. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41337-2_11.
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Addisu, Matusala, Danilo Avola, Paola Bianchi, Paolo Bottoni, Stefano Levialdi, and Emanuele Panizzi. "Annotating Significant Relations on Multimedia Web Documents." In Multimedia Information Extraction, 401–17. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118219546.ch24.
Повний текст джерелаТези доповідей конференцій з теми "Relation extractor"
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Liu, Lihan, and Pengfei Li. "Transformer with Local-feature Extractor for Relation Extraction." In 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9534183.
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Yang, Dongdong, Senzhang Wang, and Zhoujun Li. "Ensemble Neural Relation Extraction with Adaptive Boosting." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/630.
Повний текст джерелаАнотація:
Relation extraction has been widely studied to extract new relational facts from open corpus. Previous relation extraction methods are faced with the problem of wrong labels and noisy data, which substantially decrease the performance of the model. In this paper, we propose an ensemble neural network model - Adaptive Boosting LSTMs with Attention, to more effectively perform relation extraction. Specifically, our model first employs the recursive neural network LSTMs to embed each sentence. Then we import attention into LSTMs by considering that the words in a sentence do not contribute equally to the semantic meaning of the sentence. Next via adaptive boosting, we build strategically several such neural classifiers. By ensembling multiple such LSTM classifiers with adaptive boosting, we could build a more effective and robust joint ensemble neural networks based relation extractor. Experiment results on real dataset demonstrate the superior performance of the proposed model, improving F1-score by about 8% compared to the state-of-the-art models.
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Yu, Bowen, Zhenyu Zhang, Tingwen Liu, Bin Wang, Sujian Li, and Quangang Li. "Beyond Word Attention: Using Segment Attention in Neural Relation Extraction." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/750.
Повний текст джерелаАнотація:
Relation extraction studies the issue of predicting semantic relations between pairs of entities in sentences. Attention mechanisms are often used in this task to alleviate the inner-sentence noise by performing soft selections of words independently. Based on the observation that information pertinent to relations is usually contained within segments (continuous words in a sentence), it is possible to make use of this phenomenon for better extraction. In this paper, we aim to incorporate such segment information into neural relation extractor. Our approach views the attention mechanism as linear-chain conditional random fields over a set of latent variables whose edges encode the desired structure, and regards attention weight as the marginal distribution of each word being selected as a part of the relational expression. Experimental results show that our method can attend to continuous relational expressions without explicit annotations, and achieve the state-of-the-art performance on the large-scale TACRED dataset.
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Takahashi, Hideharu, Hiroshige Kikura, Kenji Takeshita, and Masanori Aritomi. "Visualization of Dispersed Phase Flow in Centrifugal Extractor Using Taylor-Couette Vortex Flow." In ASME/JSME 2011 8th Thermal Engineering Joint Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/ajtec2011-44403.
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For studying the designs and running operations of an extractor which uses Taylor-Couette vortex flow, we focused on a metal extraction system as one of the extraction models of heat generating nuclides and observed the flow patterns of dispersed phase by dyeing the phase in the extractor, and we investigated the effects of hydrophobic coating applied to the inner cylinder surface on the flow characteristics. Moreover, for the quantitative measurement and analysis of the flow field, we evaluated the applicability of Ultrasonic Velocity Profiler (UVP) to flow field measurement. Thorough these visualization methods of dispersed phase in a centrifugal extractor using Taylor-Couette vortex flow, we examined the relation between flow field and extraction characteristics of the extractor.
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Yuan, Yue, Xiaofei Zhou, Shirui Pan, Qiannan Zhu, Zeliang Song, and Li Guo. "A Relation-Specific Attention Network for Joint Entity and Relation Extraction." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/561.
Повний текст джерелаАнотація:
Joint extraction of entities and relations is an important task in natural language processing (NLP), which aims to capture all relational triplets from plain texts. This is a big challenge due to some of the triplets extracted from one sentence may have overlapping entities. Most existing methods perform entity recognition followed by relation detection between every possible entity pairs, which usually suffers from numerous redundant operations. In this paper, we propose a relation-specific attention network (RSAN) to handle the issue. Our RSAN utilizes relation-aware attention mechanism to construct specific sentence representations for each relation, and then performs sequence labeling to extract its corresponding head and tail entities. Experiments on two public datasets show that our model can effectively extract overlapping triplets and achieve state-of-the-art performance.
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Stickley, Daniel. "Relating Relations: Meta-Relation Extraction from Online Health Forum Posts." In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.eacl-srw.18.
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Barbirato, João Gabriel Melo, Livy Real, and Helena de Medeiros Caseli. "Relation extraction in structured and unstructured data: a comparative investigation on smartphone titles in the e-commerce domain." In Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/stil.2021.17789.
Повний текст джерелаАнотація:
As large amounts of unstructured data are generated on a regular basis, expressing or storing knowledge in a way that is useful remains a challenge. In this context, Relation Extraction (RE) is the task of automatically identifying relationships in unstructured textual data. Thus, we investigated the relation extraction on unstructured e-commerce data from the smartphone domain, using a BERT model fine-tuned for this task. We conducted two experiments to acknowledge how much relational information it is possible to extract from product sheets (structured data) and product titles (unstructured data), and a third experiment to compare both. Analysis shows that extracting relations within a title can retrieve correct relations that are not evident on the related sheet.
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Zhang, Ningyu, Xiang Chen, Xin Xie, Shumin Deng, Chuanqi Tan, Mosha Chen, Fei Huang, Luo Si, and Huajun Chen. "Document-level Relation Extraction as Semantic Segmentation." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/551.
Повний текст джерелаАнотація:
Document-level relation extraction aims to extract relations among multiple entity pairs from a document. Previously proposed graph-based or transformer-based models utilize the entities independently, regardless of global information among relational triples. This paper approaches the problem by predicting an entity-level relation matrix to capture local and global information, parallel to the semantic segmentation task in computer vision. Herein, we propose a Document U-shaped Network for document-level relation extraction. Specifically, we leverage an encoder module to capture the context information of entities and a U-shaped segmentation module over the image-style feature map to capture global interdependency among triples. Experimental results show that our approach can obtain state-of-the-art performance on three benchmark datasets DocRED, CDR, and GDA.
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Perera, Lokukaluge P., Brage Mo, and Matthias P. Nowak. "Visualization of Relative Wind Profiles in Relation to Actual Weather Conditions of Ship Routes." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61120.
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Ship performance and navigation data are collected by vessels that are equipped with various supervisory control and data acquisition systems (SCADA). Such information is collected as large-scale data sets, therefore various analysis tools and techniques are required to extract useful information from the same. The extracted information on ship performance and navigation conditions can be used to implement energy efficiency and emission control applications (i.e. weather routing type applications) on these vessels. Hence, this study proposes to develop data visualizing methods in order to extract ship performance and navigation information from the respective data sets in relation to weather conditions. The relative wind (i.e. apparent wind) profile (i.e. wind speed and direction) collected by onboard sensors and absolute weather conditions, which are extracted from external data sources by using position and time information a selected vessel (i.e. from the recorded ship routes), are considered. Hence, the relative wind profile of the vessel is compared with actual weather conditions to visualize ship performance and navigation parameters relationships, as the main contribution. It is believed that such relationships can be used to develop appropriate mathematical models to predict ship performance and navigation conditions under various weather conditions.
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Kuang, Jun, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao, and Aoying Zhou. "Improving Neural Relation Extraction with Implicit Mutual Relations." In 2020 IEEE 36th International Conference on Data Engineering (ICDE). IEEE, 2020. http://dx.doi.org/10.1109/icde48307.2020.00093.
Повний текст джерелаЗвіти організацій з теми "Relation extractor"
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Do, Quang X. Background Knowledge in Learning-Based Relation Extraction. Fort Belvoir, VA: Defense Technical Information Center, January 2012. http://dx.doi.org/10.21236/ada565270.
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Ward, Katrina, Jonathan Bisila, and Kelsey Cairns. Survey of Current State of the Art Entity-Relation Extraction Tools. Office of Scientific and Technical Information (OSTI), May 2020. http://dx.doi.org/10.2172/1630263.
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Ward, Katrina, Jonathan Bisila, and Kelsey Cairns. Survey of Current State of the Art Entity-Relation Extraction Tools. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1662019.
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Dorr, Bonnie, and Terry Gaasterland. Summarization-Inspired Temporal-Relation Extraction: Tense-Pair Templates and Treebank-3 Analysis. Fort Belvoir, VA: Defense Technical Information Center, December 2006. http://dx.doi.org/10.21236/ada460392.
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James, Mark, Tania Mendo, Hannah Ladd-Jones, Paddy McCann, Swithun Crowe, Alexander James Coram, and Simon Northridge. Scottish Inshore Fisheries Integrated Data System (SIFIDS): work package 5 final report identifying fishing activities and their associated drivers. Edited by Mark James and Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23451.
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[Extract from Executive Summary] The purpose of this Work Package was to: 1. Define fisher derived data collection parameters. 2. Identify and if possible, develop a quality assured system for the collection of fisher derived anecdotal and experiential information. 3. Develop an appropriate sampling design/method that could be streamed to a relational data resource. 4. Develop risk based management strategies. 5. Investigate applicable techniques/strategies for ‘change management’ regarding accurate voluntary reporting by the industry.
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Delgado, María. Political Advocacy in Colombia: Impact Evaluation of the “Building peace by securing rights for victims of conflict and violence in Colombia” project. Oxfam GB, October 2021. http://dx.doi.org/10.21201/2021.8120.
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The “Building peace by securing rights for victims of conflict and violence in Colombia” project was implemented by Oxfam in Colombia and a network of partners from 2015-2019. It focused on helping victims and Colombian human rights and peace organisations to strengthen their capacities to demand justice for rights violations and to advocate for a more favourable environment to the recognition of victim's rights. The assessment focused on the effectiveness of the project in relation to outcomes extracted from the Theory of Change. It used a combination of participatory methods and tools, the main method being process tracing, a qualitative research method that is useful for inferring causal relationships as well as contribution analysis. The report provides evidence of strengthened capacities at different levels and concludes that the advocacy work carried out as part of the project has demonstrated high levels of effectiveness. Read the full report to find out more.
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Shenker, Moshe, Paul R. Bloom, Abraham Shaviv, Adina Paytan, Barbara J. Cade-Menun, Yona Chen, and Jorge Tarchitzky. Fate of Phosphorus Originated from Treated Wastewater and Biosolids in Soils: Speciation, Transport, and Accumulation. United States Department of Agriculture, June 2011. http://dx.doi.org/10.32747/2011.7697103.bard.
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Beneficial use of reclaimed wastewater (RW) and biosolids (BS) in soils is accompanied by large input of sewage-originated P. Prolonged application may result in P accumulation up to levelsBeneficial use of reclaimed wastewater (RW) and biosolids (BS) in soils is accompanied by large input of sewage-originated P. Prolonged application may result in P accumulation up to levels that impair plant nutrition, increase P loss, and promote eutrophication in downstream waters. This study aims to shed light on the RW- and BS-P forms in soils and to follow the processes that determine P reactivity, solubility, availability, and loss in RW and BS treated soils. The Technion group used sequential P extraction combined with measuring stable oxygen isotopic composition in phosphate (δ18OP) and with 31P-NMR studies to probe P speciation and transformations in soils irrigated with RW or fresh water (FW). The application of the δ18OP method to probe inorganic P (Pi) speciation and transformations in soils was developed through collaboration between the Technion and the UCSC groups. The method was used to trace Pi in water-, NaHCO3-, NaOH-, and HCl- P fractions in a calcareous clay soil (Acre, Israel) irrigated with RW or FW. The δ18OP signature changes during a month of incubation indicated biogeochemical processes. The water soluble Pi (WSPi) was affected by enzymatic activity yielding isotopic equilibrium with the water molecules in the soil solution. Further it interacted rapidly with the NaHCO3-Pi. The more stable Pi pools also exhibited isotopic alterations in the first two weeks after P application, likely related to microbial activity. Isotopic depletion which could result from organic P (PO) mineralization was followed by enrichment which may result from biologic discrimination in the uptake. Similar transformations were observed in both soils although transformations related to biological activity were more pronounced in the soil treated with RW. Specific P compounds were identified by the Technion group, using solution-state 31P-NMR in wastewater and in soil P extracts from Acre soils irrigated by RW and FW. Few identified PO compounds (e.g., D-glucose-6-phosphate) indicated coupled transformations of P and C in the wastewater. The RW soil retained higher P content, mainly in the labile fractions, but lower labile PO, than the FW soil; this and the fact that P species in the various soil extracts of the RW soil appear independent of P species in the RW are attributed to enhanced biological activity and P recycling in the RW soil. Consistent with that, both soils retained very similar P species in the soil pools. The HUJ group tested P stabilization to maximize the environmental safe application rates and the agronomic beneficial use of BS. Sequential P extraction indicated that the most reactive BS-P forms: WSP, membrane-P, and NaHCO3-P, were effectively stabilized by ferrous sulfate (FeSul), calcium oxide (CaO), or aluminum sulfate (alum). After applying the stabilized BS, or fresh BS (FBS), FBS compost (BSC), or P fertilizer (KH2PO4) to an alluvial soil, P availability was probed during 100 days of incubation. A plant-based bioassay indicated that P availability followed the order KH2PO4 >> alum-BS > BSC ≥ FBS > CaO-BS >> FeSul-BS. The WSPi concentration in soil increased following FBS or BSC application, and P mineralization further increased it during incubation. In contrast, the chemically stabilized BS reduced WSPi concentrations relative to the untreated soil. It was concluded that the chemically stabilized BS effectively controlled WSPi in the soil while still supplying P to support plant growth. Using the sequential extraction procedure the persistence of P availability in BS treated soils was shown to be of a long-term nature. 15 years after the last BS application to MN soils that were annually amended for 20 years by heavy rates of BS, about 25% of the added BS-P was found in the labile fractions. The UMN group further probed soil-P speciation in these soils by bulk and micro X-ray absorption near edge structure (XANES). This newly developed method was shown to be a powerful tool for P speciation in soils. In a control soil (no BS added), 54% of the total P was PO and it was mostly identified as phytic acid; 15% was identified as brushite and 26% as strengite. A corn crop BS amended soil included mostly P-Fe-peat complex, variscite and Al-P-peat complex but no Ca-P while in a BS-grass soil octacalcium phosphate was identified and o-phosphorylethanolamine or phytic acid was shown to dominate the PO fraction that impair plant nutrition, increase P loss, and promote eutrophication in downstream waters. This study aims to shed light on the RW- and BS-P forms in soils and to follow the processes that determine P reactivity, solubility, availability, and loss in RW and BS treated soils. The Technion group used sequential P extraction combined with measuring stable oxygen isotopic composition in phosphate (δ18OP) and with 31P-NMR studies to probe P speciation and transformations in soils irrigated with RW or fresh water (FW). The application of the δ18OP method to probe inorganic P (Pi) speciation and transformations in soils was developed through collaboration between the Technion and the UCSC groups. The method was used to trace Pi in water-, NaHCO3-, NaOH-, and HCl- P fractions in a calcareous clay soil (Acre, Israel) irrigated with RW or FW. The δ18OP signature changes during a month of incubation indicated biogeochemical processes. The water soluble Pi (WSPi) was affected by enzymatic activity yielding isotopic equilibrium with the water molecules in the soil solution. Further it interacted rapidly with the NaHCO3-Pi. The more stable Pi pools also exhibited isotopic alterations in the first two weeks after P application, likely related to microbial activity. Isotopic depletion which could result from organic P (PO) mineralization was followed by enrichment which may result from biologic discrimination in the uptake. Similar transformations were observed in both soils although transformations related to biological activity were more pronounced in the soil treated with RW. Specific P compounds were identified by the Technion group, using solution-state 31P-NMR in wastewater and in soil P extracts from Acre soils irrigated by RW and FW. Few identified PO compounds (e.g., D-glucose-6-phosphate) indicated coupled transformations of P and C in the wastewater. The RW soil retained higher P content, mainly in the labile fractions, but lower labile PO, than the FW soil; this and the fact that P species in the various soil extracts of the RW soil appear independent of P species in the RW are attributed to enhanced biological activity and P recycling in the RW soil. Consistent with that, both soils retained very similar P species in the soil pools. The HUJ group tested P stabilization to maximize the environmental safe application rates and the agronomic beneficial use of BS. Sequential P extraction indicated that the most reactive BS-P forms: WSP, membrane-P, and NaHCO3-P, were effectively stabilized by ferrous sulfate (FeSul), calcium oxide (CaO), or aluminum sulfate (alum). After applying the stabilized BS, or fresh BS (FBS), FBS compost (BSC), or P fertilizer (KH2PO4) to an alluvial soil, P availability was probed during 100 days of incubation. A plant-based bioassay indicated that P availability followed the order KH2PO4 >> alum-BS > BSC ≥ FBS > CaO-BS >> FeSul-BS. The WSPi concentration in soil increased following FBS or BSC application, and P mineralization further increased it during incubation. In contrast, the chemically stabilized BS reduced WSPi concentrations relative to the untreated soil. It was concluded that the chemically stabilized BS effectively controlled WSPi in the soil while still supplying P to support plant growth. Using the sequential extraction procedure the persistence of P availability in BS treated soils was shown to be of a long-term nature. 15 years after the last BS application to MN soils that were annually amended for 20 years by heavy rates of BS, about 25% of the added BS-P was found in the labile fractions. The UMN group further probed soil-P speciation in these soils by bulk and micro X-ray absorption near edge structure (XANES). This newly developed method was shown to be a powerful tool for P speciation in soils. In a control soil (no BS added), 54% of the total P was PO and it was mostly identified as phytic acid; 15% was identified as brushite and 26% as strengite. A corn crop BS amended soil included mostly P-Fe-peat complex, variscite and Al-P-peat complex but no Ca-P while in a BS-grass soil octacalcium phosphate was identified and o-phosphorylethanolamine or phytic acid was shown to dominate the PO fraction.
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Castillo Parrilla, José Antonio. The Legal Regulation of Digital Wealth: Commerce, Ownership and Inheritance of Data. Universitätsbibliothek J. C. Senckenberg, Frankfurt am Main, 2021. http://dx.doi.org/10.21248/gups.64581.
Повний текст джерелаАнотація:
Digital wealth and its necessary regulation have gained prominence in recent years. The European Commission has published several documents and policy proposals relating, directly or indirectly, to the data economy. A data economy can be defined as an ecosystem of different types of market players collaborating to ensure that data is accessible and usable in order to extract value from data through, for example, creating a variety of applications with great potential to improve daily life. The value of data can increase from EUR 257 billion (1.85 of EU Gross Domestic Product (GDP)) to EUR 643 billion by 2020 (3.17% of EU GDP), according to the EU Commission. The legal implications of the increasing value of the data economy are clear; hence the need to address the challenges presented by its legal regulation.
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Gantzer, Clark J., Shmuel Assouline, and Stephen H. Anderson. Synchrotron CMT-measured soil physical properties influenced by soil compaction. United States Department of Agriculture, February 2006. http://dx.doi.org/10.32747/2006.7587242.bard.
Повний текст джерелаАнотація:
Methods to quantify soil conditions of pore connectivity, tortuosity, and pore size as altered by compaction were done. Air-dry soil cores were scanned at the GeoSoilEnviroCARS sector at the Advanced Photon Source for x-ray computed microtomography of the Argonne facility. Data was collected on the APS bending magnet Sector 13. Soil sample cores 5- by 5-mm were studied. Skeletonization algorithms in the 3DMA-Rock software of Lindquist et al. were used to extract pore structure. We have numerically investigated the spatial distribution for 6 geometrical characteristics of the pore structure of repacked Hamra soil from three-dimensional synchrotron computed microtomography (CMT) computed tomographic images. We analyzed images representing cores volumes 58.3 mm³ having average porosities of 0.44, 0.35, and 0.33. Cores were packed with < 2mm and < 0.5mm sieved soil. The core samples were imaged at 9.61-mm resolution. Spatial distributions for pore path length and coordination number, pore throat size and nodal pore volume obtained. The spatial distributions were computed using a three-dimensional medial axis analysis of the void space in the image. We used a newly developed aggressive throat computation to find throat and pore partitioning for needed for higher porosity media such as soil. Results show that the coordination number distribution measured from the medial axis were reasonably fit by an exponential relation P(C)=10⁻C/C0. Data for the characteristic area, were also reasonably well fit by the relation P(A)=10⁻ᴬ/ᴬ0. Results indicates that compression preferentially affects the largest pores, reducing them in size. When compaction reduced porosity from 44% to 33%, the average pore volume reduced by 30%, and the average pore-throat area reduced by 26%. Compaction increased the shortest paths interface tortuosity by about 2%. Soil structure alterations induced by compaction using quantitative morphology show that the resolution is sufficient to discriminate soil cores. This study shows that analysis of CMT can provide information to assist in assessment of soil management to ameliorate soil compaction.
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Saldanha, Ian J., Wangnan Cao, Justin M. Broyles, Gaelen P. Adam, Monika Reddy Bhuma, Shivani Mehta, Laura S. Dominici, Andrea L. Pusic, and Ethan M. Balk. Breast Reconstruction After Mastectomy: A Systematic Review and Meta-Analysis. Agency for Healthcare Research and Quality (AHRQ), July 2021. http://dx.doi.org/10.23970/ahrqepccer245.
Повний текст джерелаАнотація:
Objectives. This systematic review evaluates breast reconstruction options for women after mastectomy for breast cancer (or breast cancer prophylaxis). We addressed six Key Questions (KQs): (1) implant-based reconstruction (IBR) versus autologous reconstruction (AR), (2) timing of IBR and AR in relation to chemotherapy and radiation therapy, (3) comparisons of implant materials, (4) comparisons of anatomic planes for IBR, (5) use versus nonuse of human acellular dermal matrices (ADMs) during IBR, and (6) comparisons of AR flap types. Data sources and review methods. We searched Medline®, Embase®, Cochrane CENTRAL, CINAHL®, and ClinicalTrials.gov from inception to March 23, 2021, to identify comparative and single group studies. We extracted study data into the Systematic Review Data Repository Plus (SRDR+). We assessed the risk of bias and evaluated the strength of evidence (SoE) using standard methods. The protocol was registered in PROSPERO (registration number CRD42020193183). Results. We found 8 randomized controlled trials, 83 nonrandomized comparative studies, and 69 single group studies. Risk of bias was moderate to high for most studies. KQ1: Compared with IBR, AR is probably associated with clinically better patient satisfaction with breasts and sexual well-being but comparable general quality of life and psychosocial well-being (moderate SoE, all outcomes). AR probably poses a greater risk of deep vein thrombosis or pulmonary embolism (moderate SoE), but IBR probably poses a greater risk of reconstructive failure in the long term (1.5 to 4 years) (moderate SoE) and may pose a greater risk of breast seroma (low SoE). KQ 2: Conducting IBR either before or after radiation therapy may result in comparable physical well-being, psychosocial well-being, sexual well-being, and patient satisfaction with breasts (all low SoE), and probably results in comparable risks of implant failure/loss or need for explant surgery (moderate SoE). We found no evidence addressing timing of IBR or AR in relation to chemotherapy or timing of AR in relation to radiation therapy. KQ 3: Silicone and saline implants may result in clinically comparable patient satisfaction with breasts (low SoE). There is insufficient evidence regarding double lumen implants. KQ 4: Whether the implant is placed in the prepectoral or total submuscular plane may not be associated with risk of infections that are not explicitly implant related (low SoE). There is insufficient evidence addressing the comparisons between prepectoral and partial submuscular and between partial and total submuscular planes. KQ 5: The evidence is inconsistent regarding whether human ADM use during IBR impacts physical well-being, psychosocial well-being, or satisfaction with breasts. However, ADM use probably increases the risk of implant failure/loss or need for explant surgery (moderate SoE) and may increase the risk of infections not explicitly implant related (low SoE). Whether or not ADM is used probably is associated with comparable risks of seroma and unplanned repeat surgeries for revision (moderate SoE for both), and possibly necrosis (low SoE). KQ 6: AR with either transverse rectus abdominis (TRAM) or deep inferior epigastric perforator (DIEP) flaps may result in comparable patient satisfaction with breasts (low SoE), but TRAM flaps probably increase the risk of harms to the area of flap harvest (moderate SoE). AR with either DIEP or latissimus dorsi flaps may result in comparable patient satisfaction with breasts (low SoE), but there is insufficient evidence regarding thromboembolic events and no evidence regarding other surgical complications. Conclusion. Evidence regarding surgical breast reconstruction options is largely insufficient or of only low or moderate SoE. New high-quality research is needed, especially for timing of IBR and AR in relation to chemotherapy and radiation therapy, for comparisons of implant materials, and for comparisons of anatomic planes of implant placement.