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Journal articles on the topic 'Relation extractor'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Yuan, Yujin, Liyuan Liu, Siliang Tang, et al. "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.

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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 m

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Zhang, Congle, Raphael Hoffmann, and Daniel Weld. "Ontological Smoothing for Relation Extraction with Minimal Supervision." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 157–63. http://dx.doi.org/10.1609/aaai.v26i1.8102.

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Relation extraction, the process of converting natural language text into structured knowledge, is increasingly important. Most successful techniques use supervised machine learning to generate extractors from sentences that have been manually labeled with the relations' arguments. Unfortunately, these methods require numerous training examples, which are expensive and time-consuming to produce. This paper presents ontological smoothing, a semi-supervisedtechnique that learns extractors for a set of minimally-labeledrelations. Ontological smoothing has three phases. First, itgenerates a mappin

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Peng, Rao, Litian Huang, and Xinguo Yu. "Solving Arithmetic Word Problems by Synergizing Large Language Model and Scene-Aware Syntax–Semantics Method." Applied Sciences 14, no. 18 (2024): 8184. http://dx.doi.org/10.3390/app14188184.

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Developing Arithmetic Word Problem (AWP) -solving algorithms has recently become one of the hottest research areas because it can simultaneously advance general artificial intelligence and the application of AI technology in education. This paper presents a novel algorithm for solving AWPs by synergizing Large Language Models (LLMs) with the Scene-Aware Syntax–Semantics (S2) method. The innovation of this algorithm lies in leveraging the LLM to divide problems into multiple scenes, thereby enhancing the relation-flow approach in the processes of relation extraction and reasoning. Our algorithm

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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 (2021): 12060. http://dx.doi.org/10.3390/app112412060.

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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

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Halike, Ayiguli, Aishan Wumaier, and Tuergen Yibulayin. "Zero-Shot Relation Triple Extraction with Prompts for Low-Resource Languages." Applied Sciences 13, no. 7 (2023): 4636. http://dx.doi.org/10.3390/app13074636.

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Although low-resource relation extraction is vital in knowledge construction and characterization, more research is needed on the generalization of unknown relation types. To fill the gap in the study of low-resource (Uyghur) relation extraction methods, we created a zero-shot with a quick relation extraction task setup. Each triplet extracted from an input phrase consists of the subject, relation type, and object. This paper suggests generating structured texts by urging language models to provide related instances. Our model consists of two modules: relation generator and relation and triple

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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 (2020): 1181. http://dx.doi.org/10.3390/app10031181.

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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’ relati

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Cao, Han, Lingwei Wei, Wei Zhou, and Songlin Hu. "Enhancing Multi-Hop Fact Verification with Structured Knowledge-Augmented Large Language Models." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 22 (2025): 23514–22. https://doi.org/10.1609/aaai.v39i22.34520.

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The rapid development of social platforms exacerbates the dissemination of misinformation, which stimulates the research in fact verification. Recent studies tend to leverage semantic features to solve this problem as a single-hop task. However, the process of verifying a claim requires several pieces of evidence with complicated inner logic and relations to verify the given claim in real-world situations. Recent studies attempt to improve both understanding and reasoning abilities to enhance the performance, but they overlook the crucial relations between entities that benefit models to under

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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 (2009): 1259–67. http://dx.doi.org/10.1590/s0100-06832009000500019.

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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 wer

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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.

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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

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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.

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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 mod

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Song, Wei, and Zijiang Yang. "Improving Distantly Supervised Relation Extraction with Multi-Level Noise Reduction." AI 5, no. 3 (2024): 1709–30. http://dx.doi.org/10.3390/ai5030084.

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Background: Distantly supervised relation extraction (DSRE) aims to identify semantic relations in large-scale texts automatically labeled via knowledge base alignment. It has garnered significant attention due to its high efficiency, but existing methods are plagued by noise at both the word and sentence level and fail to address these issues adequately. The former level of noise arises from the large proportion of irrelevant words within sentences, while noise at the latter level is caused by inaccurate relation labels for various sentences. Method: We propose a novel multi-level noise reduc

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H. L. Kushwaha, A.P. Srivastava, and Harpal Singh. "Influence of Crop and Machine Parameters on the Performance of Okra Seed Extractor in Relation to Seed Quality." Journal of Agricultural Engineering (India) 41, no. 3 (2004): 26–30. http://dx.doi.org/10.52151/jae2004413.1089.

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Studies were conducted on the effect of different cylinder speeds (5. 6 and 7 m/s). concave clearances (7. 10 and 13 mm). moisture contents (12.3, 15.8 and 18.8 % d.b.) and type of extraction mechanism on _quality. Three types of extractor drums, viz. square head bolted drum. rubberised and rasp bar used for seed extraction. Seed quality was evaluated for vigour index. dead seed, and germination at the constant feed rate of 70 kg/h. It was found that germination and vigour of seeds decreased with increase in pod moisture content The germination decreased with increase in cylinder speed, wherea

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Zhong, Yi, Weize Quan, Dong-Ming Yan, Jie Jiang, and Yingmei Wei. "PointCFormer: A Relation-Based Progressive Feature Extraction Network for Point Cloud Completion." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 10 (2025): 10689–97. https://doi.org/10.1609/aaai.v39i10.33161.

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Point cloud completion aims to reconstruct the complete 3D shape from incomplete point clouds, and it is crucial for tasks such as 3D object detection and segmentation. Despite the continuous advances in point cloud analysis techniques, feature extraction methods are still confronted with apparent limitations. The sparse sampling of point clouds, used as inputs in most methods, often results in a certain loss of global structure information. Meanwhile, traditional local feature extraction methods usually struggle to capture the intricate geometric details. To overcome these drawbacks, we intro

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Safina, Al’bina V., Dilara F. Ziatdinova, Leysan R. Nazipova, Rushan G. Safin, and Kirill V. Valeev. "The Engineering Procedure for Calculating the Plant for Betulin Extraction from Birch Bark." Lesnoy Zhurnal (Forestry Journal), no. 1 (February 10, 2024): 195–207. http://dx.doi.org/10.37482/0536-1036-2024-1-195-207.

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The analysis of the current state of the process of betulin extraction from birch bark has shown the relevance of the implementation of periodic extraction technology using toluene as a solvent at small enterprises of the timber industry complex. This article presents the scheme of an extraction plant consisting of an extractor, an evaporator, a condenser, a florentine flask, an extract collector, as well as the principle of the plant operation. The extraction process is carried out in two stages: when the raw material is at rest in relation to toluene and when the raw material is extracted by

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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 (2017): 1628–31. http://dx.doi.org/10.37358/rc.17.7.5731.

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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 allowe

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Wu, Ming-Jui, Wei-Ling Chen, Chung-Dann Kan, et al. "Dysfunction Screening in Experimental Arteriovenous Grafts for Hemodialysis Using Fractional-Order Extractor and Color Relation Analysis." Cardiovascular Engineering and Technology 6, no. 4 (2015): 463–73. http://dx.doi.org/10.1007/s13239-015-0239-5.

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Choi, Won-Hyuk, and Yong-Suk Choi. "Effective Pre-Training Method and Its Compositional Intelligence for Image Captioning." Sensors 22, no. 9 (2022): 3433. http://dx.doi.org/10.3390/s22093433.

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With the increase in the performance of deep learning models, the model parameter has increased exponentially. An increase in model parameters leads to an increase in computation and training time, i.e., an increase in training cost. To reduce the training cost, we propose Compositional Intelligence (CI). This is a reuse method that combines pre-trained models for different tasks. Since the CI uses a well-trained model, good performance and small training cost can be expected in the target task. We applied the CI to the Image Captioning task. Compared to using a trained feature extractor, the

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Neha, Verma, Singh Ajeet, and Pratap Singh Atul. "AN AUTOMATIC SPEECH RECOGNITION APPROACH USING MODIFIED VOICE ACTIVITY DETECTION MECHANISM." International Journal of Engineering Sciences & Emerging Technologies 11, no. 2 (2023): 108–14. https://doi.org/10.5281/zenodo.10435452.

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<em>The effectiveness of Automatic Speech Recognition (ASR), which can be employed in loud circumstances, is being researched. The effectiveness of common parameterization methods was evaluated in relation to lustiness and compared to the background signal. By merging the essential components of PLP and MFCC, a hybrid feature extractor is created for Mel frequency cepstral coefficients (MFCC), Perceptual linear predictive (PLP) coefficients, and their modified forms. Only the ASR method's training phase was used to apply the VAD-based frame dropping calculation. This technique has the benefit

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Bernal, Dionisio, and Martin D. Ulriksen. "Quadratic Basis Pursuit in Model Updating of Underconstrained Problems." Journal of Physics: Conference Series 2647, no. 25 (2024): 252001. http://dx.doi.org/10.1088/1742-6596/2647/25/252001.

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Abstract This paper considers the extraction of sparse solutions using the L1 minimization surrogate for two approximations of the nonlinear relation between parameters and features; in the first, nonline-arity is discarded altogether and in the second a quadratic relation is assumed. The associated algorithms are the well-known Basis Pursuit (BP) and the more recently introduced Quadratic Basis Pursuit (QBP). It is contended that measuring success by comparing the extracted solutions with the underlying truth is unnecessary, as all that’s needed from the extractor is to identify a sufficientl

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Tang, Xue-song, Luchao Jiang, Kuangrong Hao, Tong Wang, and Xiaoyan Liu. "A Moth–Flame Optimized Echo State Network and Triplet Feature Extractor for Epilepsy Electro-Encephalography Signals." Mathematics 11, no. 6 (2023): 1438. http://dx.doi.org/10.3390/math11061438.

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The analysis of epilepsy electro-encephalography (EEG) signals is of great significance for the diagnosis of epilepsy, which is one of the common neurological diseases of all age groups. With the developments of machine learning, many data-driven models have achieved great performance in EEG signals classification. However, it is difficult to select appropriate hyperparameters for the models to file a specific task. In this paper, an evolutionary algorithm enhanced model is proposed, which optimizes the fixed weights of the reservoir layer of the echo state network (ESN) according to the speci

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Klepach, Halyna, Svitlana Voloshanska, Halyna Kovalchuk, and Aniela Stopa. "BIOLOGICALLY ACTIVE PROPERTIES OF THE ETHANOL AND AQUEOUS EXTRACTS FROM THE NEEDLES OF JUNIPERUS COMMUNIS." Scientific Journal of Polonia University 34, no. 3 (2019): 104–12. http://dx.doi.org/10.23856/3413.

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The authors have tested different methods for preparing ethanol and aqueous extracts from the needles of the natural forms of the common juniper and researched some of their biologically active properties. They found 70% ethanol to be the best extractor of bioactive substances from the needles of the common juniper in contrast to 50% and 30% ethanol. They prove that the optimal way to obtain alcohol extracts is crushing the needles of the common juniper to linear sizes: 0.5-2 mm and to infuse in 70 % of ethanol for at least 20 days. Alcohol extracts obtained in this way (10%, g/g) contain poly

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Cheng, Rui, and Qing Li. "Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 1 (2021): 55–62. http://dx.doi.org/10.1609/aaai.v35i1.16077.

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In finance, the momentum spillovers of listed firms is well acknowledged. Only few studies predicted the trend of one firm in terms of its relevant firms. A common strategy of the pilot work is to adopt graph convolution networks (GCNs) with some predefined firm relations. However, momentum spillovers are propagated via a variety of firm relations, of which the bridging importance varies with time. Restricting to several predefined relations inevitably makes noise and thus misleads stock predictions. In addition, traditional GCNs transfer and aggregate the peer influences without considering t

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Chen, Yile, Xiucheng Li, Gao Cong, et al. "Points-of-interest relationship inference with spatial-enriched graph neural networks." Proceedings of the VLDB Endowment 15, no. 3 (2021): 504–12. http://dx.doi.org/10.14778/3494124.3494134.

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As a fundamental component in location-based services, inferring the relationship between points-of-interests (POIs) is very critical for service providers to offer good user experience to business owners and customers. Most of the existing methods for relationship inference are not targeted at POI, thus failing to capture unique spatial characteristics that have huge effects on POI relationships. In this work we propose PRIM to tackle POI relationship inference for multiple relation types. PRIM features four novel components, including a weighted relational graph neural network, category taxo

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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.

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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

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Ma, Meng, Arielle Redfern, Xiang Zhou, et al. "Automated abstraction of real-world clinical outcome in lung cancer: A natural language processing and artificial intelligence approach from electronic health records." Journal of Clinical Oncology 38, no. 15_suppl (2020): e14062-e14062. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e14062.

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e14062 Background: Real world evidence generated from electronic health records (EHRs) is playing an increasing role in health care decisions. It has been recognized as an essential element to assess cancer outcomes in real-world settings. Automatically abstracting outcomes from notes is becoming a fundamental challenge in medical informatics. In this study, we aim to develop a system to automatically abstract outcomes (Progression, Response, Stable Disease) from notes in lung cancer. Methods: A lung cancer cohort (n = 5,003) was obtained from the Mount Sinai Data Warehouse. The progress, path

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Bardanis, Michael, Sofia Grifiza, Dimitrios Kokoviadis, and Marianna Feuillas. "The combination of splitting tensile strength and unconfined compression tests on unsaturated soils to measure the evolution of unsaturated shear strength." E3S Web of Conferences 382 (2023): 04001. http://dx.doi.org/10.1051/e3sconf/202338204001.

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The paper presents experimental results from unconfined compression and splitting tensile tests used in combination in order to estimate the cohesion intercept of unsaturated soils. Samples of different soils in the form of slurry were subjected to various suction values using the axis translation technique in a pressure plate extractor and then these samples were removed and subjected to unconfined compression and splitting tensile tests. Mohr’ circles for the two loading conditions were drawn and the tangents plotted in order to obtain the cohesion intercept for each soil and each suction. C

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Yadav, Shweta, Usha Lokala, Raminta Daniulaityte, Krishnaprasad Thirunarayan, Francois Lamy, and Amit Sheth. "“When they say weed causes depression, but it’s your fav antidepressant”: Knowledge-aware attention framework for relationship extraction." PLOS ONE 16, no. 3 (2021): e0248299. http://dx.doi.org/10.1371/journal.pone.0248299.

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With the increasing legalization of medical and recreational use of cannabis, more research is needed to understand the association between depression and consumer behavior related to cannabis consumption. Big social media data has potential to provide deeper insights about these associations to public health analysts. In this interdisciplinary study, we demonstrate the value of incorporating domain-specific knowledge in the learning process to identify the relationships between cannabis use and depression. We develop an end-to-end knowledge infused deep learning framework (Gated-K-BERT) that

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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 (2017): 87–93. http://dx.doi.org/10.31436/iiumej.v18i2.802.

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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,

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Husna, Shifa Aulia, Mochamad Hadi, and Rully Rahadian. "Struktur Komunitas Mikroartropoda Tanah di Lahan Pertanian Organik dan Anorganik di Desa Batur Kecamatan Getasan Salatiga." Bioma : Berkala Ilmiah Biologi 18, no. 2 (2016): 157. http://dx.doi.org/10.14710/bioma.18.2.157-166.

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Soil microarthropods is a arthropods that have an important role in decomposing organic materials and soil nutrients. On the farmland there is organic materials content and soil nutrients that abundants enough, because the addition of manure as a source of energy in the ground. The research was conducted in August-October 2015 took place in the field of organic and inorganic farmland in the Batur Village, Getasan Sub-district, Salatiga. This study aimed to examine the soil microarthropods community structure in organic and inorganic farmland as well as the effect of chemical and physical envir

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Husna, Shifa Aulia, Mochamad Hadi, and Rully Rahadian. "Struktur Komunitas Mikroartropoda Tanah di Lahan Pertanian Organik dan Anorganik di Desa Batur Kecamatan Getasan Salatiga." Bioma : Berkala Ilmiah Biologi 18, no. 2 (2017): 164. http://dx.doi.org/10.14710/bioma.18.2.164-173.

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Soil microarthropods is a arthropods that have an important role in decomposing organic materials and soil nutrients. On the farmland there is organic materials content and soil nutrients that abundants enough, because the addition of manure as a source of energy in the ground. The research was conducted in August-October 2015 took place in the field of organic and inorganic farmland in the Batur Village, Getasan Sub-district, Salatiga. This study aimed to examine the soil microarthropods community structure in organic and inorganic farmland as well as the effect of chemical and physical envir

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Qu, R. L., D. Li, R. Du, and R. Qu. "Lead Uptake by Roots of Four Turfgrass Species in Hydroponic Cultures." HortScience 38, no. 4 (2003): 623–26. http://dx.doi.org/10.21273/hortsci.38.4.623.

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Turfgrass, which is widely grown and produces a large amount of biomass, could act as a sink for industrial pollutants in urban and suburban regions. Little research has been conducted regarding heavy metal uptake by turfgrasses. The objective of this study was to evaluate root uptake of lead (Pb) in four turfgrass species. Grasses were grown hydroponically in solutions containing from 0 to 450 mg·L-1 Pb, at either pH 4.5 or 5.5, for 4 or 8 days. A significant quadratic relation existed between Pb accumulation in roots and solution Pb concentration within the tested range. The maximum Pb accum

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Delgado-Plaza, Emérita, Miguel Quilambaqui, Juan Peralta-Jaramillo, Hector Apolo, and Borja Velázquez-Martí. "Estimation of the Energy Consumption of the Rice and Corn Drying Process in the Equatorial Zone." Applied Sciences 10, no. 21 (2020): 7497. http://dx.doi.org/10.3390/app10217497.

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Drying is considered one of the industrial processes that requires more energy than other processes, being a topic of much interest to the agricultural sector, especially the evaluation of energy consumption for rice and corn dryers. To meet this goal, an overview survey matrix and protocols for temperature measurements of dryers were developed. The study evaluated 49 rice dryers and 14 yellow corn dryers. As a result, it was determined that the oversizing of the fan/extractor and the dryer engine generates a high energy consumption, added to the lack of insulation in the heat ducts. Therefore

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Zhang, Bo, Tao Zhang, Yuanyuan Ma, et al. "A Low-Latency Approach for RFF Identification in Open-Set Scenarios." Electronics 13, no. 2 (2024): 384. http://dx.doi.org/10.3390/electronics13020384.

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Radio frequency fingerprint (RFF) identification represents a promising technique for lightweight device authentication. However, current research on RFF primarily focuses on the close-set recognition assumption. Moreover, the high computational complexity and excessive latency during the identification stage represent an intolerable burden for Internet of Things (IoT) devices. In this paper, we propose a deep-learning-based RFF identification framework in relation to open-set scenarios. Specifically, we leverage a simulated training scheme, in which we strategically designate certain devices

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Zakria, Gehad, Mamdouh Farouk, Khaled Fathy, and Malak N. Makar. "Relation Extraction from Arabic Wikipedia." Indian Journal of Science and Technology 12, no. 46 (2019): 01–06. http://dx.doi.org/10.17485/ijst/2019/v12i46/147512.

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Zhang, Lei. "Study of Educational Information Resource Download Quality with Optimal Symmetrical Interval Solution of Fuzzy Relation Inequality in the Format of a System of Differential Equations." Mathematics 13, no. 10 (2025): 1602. https://doi.org/10.3390/math13101602.

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The min–max fuzzy relation inequalities are currently considered for representing the place-to-place (P2P) education knowledge, including resource sharing from one terminal to another. One terminal is the acceptor—receiving information—while the other terminal is the sink resource for educational information sharing, acting like an extractor. In the current manuscript, the idea of sharing educational information is established in the form of a dynamical system in which the unknown quantities represent the quality of downloading educational resources on different terminals. The download quality

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Zhou, Deyu, Dayou Zhong, and Yulan He. "Biomedical Relation Extraction: From Binary to Complex." Computational and Mathematical Methods in Medicine 2014 (2014): 1–18. http://dx.doi.org/10.1155/2014/298473.

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Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more th

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Galárraga-Espinosa, Daniela, Nabila Aghanim, Mathieu Langer, Céline Gouin, and Nicola Malavasi. "Populations of filaments from the distribution of galaxies in numerical simulations." Astronomy & Astrophysics 641 (September 2020): A173. http://dx.doi.org/10.1051/0004-6361/202037986.

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We present a statistical study of the filamentary structures of the cosmic web in the large hydro-dynamical simulations Illustris-TNG, Illustris, and Magneticum at redshift z = 0. We focus on the radial distribution of the galaxy density around filaments detected using the Discrete Persistent Structure Extractor (DisPerSE). We show that the average profile of filaments presents an excess of galaxy density (> 5σ) up to radial distances of 27 Mpc from the core. The relation between galaxy density and the length of filaments is further investigated showing that short (Lf < 9 Mpc) and long (

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Aguiar, Camila Zacche de, Davidson Cury, and Amal Zouaq. "Minerando Mapa Conceitual a partir de Texto em Português." Revista Brasileira de Informática na Educação 27, no. 01 (2019): 83. http://dx.doi.org/10.5753/rbie.2019.27.01.83.

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Concept maps are graphical tools for representation and construction of knowledge. The manual construction of a concept map requires time and cognitive effort, this being increased when the map should not represent the cognitive structure of the author, but rather, the information expressed in a text written by another author. Therefore, we propose a computational approach for concept map mining from texts in Portuguese that aims to represent the text in summary form through concepts and relationships. To this end, we define a technological architecture that includes the services of: (i) text

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Shaheer, Rizana, and Malu U. "Real-Time Video Violence Detection Using CNN." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 2586–90. http://dx.doi.org/10.22214/ijraset.2023.52182.

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Abstract: In order to effectively enforce the law and keep cities secure, monitoring technologies that detect violent events are becoming increasingly important. In computer vision, the practice of action recognition has gained popularity. In the field of computer vision, action recognition has gained popularity. The action recognition group, however, has mainly concentrated on straightforward activities like clapping, walking, jogging, etc. Comparatively little study has been done on identifying specific occurrences that have immediate practical applications, like fighting or violent behavior

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HACHEY, B., C. GROVER, and R. TOBIN. "Datasets for generic relation extraction." Natural Language Engineering 18, no. 1 (2011): 21–59. http://dx.doi.org/10.1017/s1351324911000106.

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AbstractA 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 or RDF triplestore that can be more effectively used for querying and automated reasoning. A number of resources have been developed for training and evaluating automatic systems for relation extraction in different domains. However, comparative evaluation is impeded by the fact that these corpora use different markup for

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Gallo, Monica, Andrea Formato, Gaetano Formato, and Daniele Naviglio. "Comparison between Two Solid-Liquid Extraction Methods for the Recovery of Steviol Glycosides from Dried Stevia Leaves Applying a Numerical Approach." Processes 6, no. 8 (2018): 105. http://dx.doi.org/10.3390/pr6080105.

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Abstract: Stevia rebaudiana Bertoni is a perennial shrub belonging to the Asteraceae family. The leaves contain a mixture of steviol glycosides with extraordinary sweetening properties, among which the most important are stevioside and rebaudioside A. These components have a high sweetening power, which is about 300 times that of sucrose, and a negligible calorie content. However, their extraction and purification are not easy. In this paper, the extraction technique under cyclic pressure, known as rapid solid-liquid dynamic extraction (RSLDE), was compared using a Naviglio extractor (NE) with

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Lorenzen, Marc C., Armin A. Weiser, Robert Pieper, Monika Lahrssen-Wiederholt, and Jorge Numata. "Introducing the Rapid Alert Supply Network Extractor (RASNEX) tool to mine supply chain information from food and feed contamination notifications in Europe." PLOS ONE 16, no. 7 (2021): e0254301. http://dx.doi.org/10.1371/journal.pone.0254301.

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Background During food or feed contamination events, it is of utmost importance to ensure their rapid resolution to minimize impact on human health, animal health and finances. The existing Rapid Alert System for Food and Feed (RASFF) is used by the European Commission, national competent authorities of member countries and the European Food Safety Authority to report information on any direct or indirect human health risk arising from food or feed, or serious risks to animal health or the environment in relation to feed. Nevertheless, no methods exist to to collectively evaluate this vast sou

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BOURGAIN, J. "MORE ON THE SUM-PRODUCT PHENOMENON IN PRIME FIELDS AND ITS APPLICATIONS." International Journal of Number Theory 01, no. 01 (2005): 1–32. http://dx.doi.org/10.1142/s1793042105000108.

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In this paper we establish new estimates on sum-product sets and certain exponential sums in finite fields of prime order. Our first result is an extension of the sum-product theorem from [8] when sets of different sizes are involed. It is shown that if [Formula: see text] and pε < |B|, |C| < |A| < p1-ε, then |A + B| + |A · C| > pδ (ε)|A|. Next we exploit the Szemerédi–Trotter theorem in finite fields (also obtained in [8]) to derive several new facts on expanders and extractors. It is shown for instance that the function f(x,y) = x(x+y) from [Formula: see text] to [Formula: see te

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Min, Bonan, Shuming Shi, Ralph Grishman, and Chin-Yew Lin. "Towards Large-Scale Unsupervised Relation Extraction from the Web." International Journal on Semantic Web and Information Systems 8, no. 3 (2012): 1–23. http://dx.doi.org/10.4018/jswis.2012070101.

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The Web brings an open-ended set of semantic relations. Discovering the significant types is very challenging. Unsupervised algorithms have been developed to extract relations from a corpus without knowing the relation types in advance, but most rely on tagging arguments of predefined types. One recently reported system is able to jointly extract relations and their argument semantic classes, taking a set of relation instances extracted by an open IE (Information Extraction) algorithm as input. However, it cannot handle polysemy of relation phrases and fails to group many similar (“synonymous”

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Drury, Brett, Hugo Gonçalo Oliveira, and Alneu de Andrade Lopes. "A survey of the extraction and applications of causal relations." Natural Language Engineering 28, no. 3 (2022): 361–400. http://dx.doi.org/10.1017/s135132492100036x.

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AbstractCausationin written natural language can express a strong relationship between events and facts. Causation in the written form can be referred to as a causal relation where a cause event entails the occurrence of an effect event. A cause and effect relationship is stronger than a correlation between events, and therefore aggregated causal relations extracted from large corpora can be used in numerous applications such as question-answering and summarisation to produce superior results than traditional approaches. Techniques like logical consequence allow causal relations to be used in

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Huynh, Nghia Huu, Quoc Bao Ho, and Te An Nguyen. "An approach in health relation extraction." Science & Technology Development Journal - Economics - Law and Management 1, Q3 (2017): 51–63. http://dx.doi.org/10.32508/stdjelm.v1iq3.449.

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Extracting relations among medical concepts is very important in the medical field. The relations denote the events or the possible relations between the concepts. Information about these relations provides users with a full view of medical problems. This helps physicians and health-care practitioners make effective decisions and minimize errors in the treatment process. This paper collects methods for relations extraction in health texts and presents an approach on one type of specific relation (i.e. template filling). The approach combines methods including rule-based and machine learningbas

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Zhang, Xinsong, Pengshuai Li, Weijia Jia, and Hai Zhao. "Multi-Labeled Relation Extraction with Attentive Capsule Network." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7484–91. http://dx.doi.org/10.1609/aaai.v33i01.33017484.

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To disclose overlapped multiple relations from a sentence still keeps challenging. Most current works in terms of neural models inconveniently assuming that each sentence is explicitly mapped to a relation label, cannot handle multiple relations properly as the overlapped features of the relations are either ignored or very difficult to identify. To tackle with the new issue, we propose a novel approach for multi-labeled relation extraction with capsule network which acts considerably better than current convolutional or recurrent net in identifying the highly overlapped relations within an in

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Peng, Nanyun, Hoifung Poon, Chris Quirk, Kristina Toutanova, and Wen-tau Yih. "Cross-Sentence N-ary Relation Extraction with Graph LSTMs." Transactions of the Association for Computational Linguistics 5 (December 2017): 101–15. http://dx.doi.org/10.1162/tacl_a_00049.

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Past work in relation extraction has focused on binary relations in single sentences. Recent NLP inroads in high-value domains have sparked interest in the more general setting of extracting n-ary relations that span multiple sentences. In this paper, we explore a general relation extraction framework based on graph long short-term memory networks (graph LSTMs) that can be easily extended to cross-sentence n-ary relation extraction. The graph formulation provides a unified way of exploring different LSTM approaches and incorporating various intra-sentential and inter-sentential dependencies, s

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Lai, Qinghan, Zihan Zhou, and Song Liu. "Joint Entity-Relation Extraction via Improved Graph Attention Networks." Symmetry 12, no. 10 (2020): 1746. http://dx.doi.org/10.3390/sym12101746.

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Joint named entity recognition and relation extraction is an essential natural language processing task that aims to identify entities and extract the corresponding relations in an end-to-end manner. At present, compared with the named entity recognition task, the relation extraction task performs poorly on complex text. To solve this problem, we proposed a novel joint model named extracting Entity-Relations viaImproved Graph Attention networks (ERIGAT), which enhances the ability of the relation extraction task. In our proposed model, we introduced the graph attention network to extract entit

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Gao, Chuhan, Guixian Xu, and Yueting Meng. "Integrated Extraction of Entities and Relations via Attentive Graph Convolutional Networks." Electronics 13, no. 22 (2024): 4373. http://dx.doi.org/10.3390/electronics13224373.

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For information security, entity and relation extraction can be applied in sensitive information protection, data leakage detection, and other aspects. The current approaches to entity relation extraction not only ignore the relevance and dependency between name entity recognition and relation extraction but also may result in the cumulative propagation of errors. To solve this problem, it is proposed that an end-to-end joint entity and relation extraction model based on the Attention mechanism and Graph Convolutional Network (GCN) to simultaneously extract named entities and their relationshi

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