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Academic literature on the topic 'Semantic pivot'

Author: Grafiati

Published: 20 April 2024

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Journal articles on the topic "Semantic pivot"

Li, Liang, Weirui Ye, Mingsheng Long, Yateng Tang, Jin Xu, and Jianmin Wang. "Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 8220–27. http://dx.doi.org/10.1609/aaai.v34i05.6336.

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Cross-domain sentiment classification aims to leverage useful knowledge from a source domain to mitigate the supervision sparsity in a target domain. A series of approaches depend on the pivot features that behave similarly for polarity prediction in both domains. However, the engineering of such pivot features remains cumbersome and prevents us from learning the disentangled and transferable representations from rich semantic and syntactic information. Towards learning the pivots and representations simultaneously, we propose a new Transferable Pivot Transformer (TPT). Our model consists of two networks: a Pivot Selector that learns to detect transferable n-gram pivots from contexts, and a Transferable Transformer that learns to generate domain-invariant representations by modeling the correlation between pivot and non-pivot words. The Pivot Selector and Transferable Transformer are jointly optimized through end-to-end back-propagation. We experiment with real tasks of cross-domain sentiment classification over 20 domain pairs where our model outperforms prior arts.

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Velleman, Dan, David Beaver, Emilie Destruel, Dylan Bumford, Edgar Onea, and Liz Coppock. "It-clefts are IT (Inquiry Terminating) constructions." Semantics and Linguistic Theory 22 (September 3, 2012): 441. http://dx.doi.org/10.3765/salt.v22i0.2640.

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We offer a new analysis of the semantics of the English it-cleft, building on recent work on exclusive particles such as "only." The analysis emphasizes the discourse function of clefts — which, we claim, is to terminate a line of inquiry by marking an answer as complete. It accounts for the semantic effects — not previously appreciated — of focus placement within the cleft pivot. It also provides a solution to a previously discussed problem with the projection of exhaustivity from embedded contexts.

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Castro-Bleda, Maria Jose, Eszter Iklódi, Gábor Recski, and Gábor Borbély. "Towards a Universal Semantic Dictionary." Applied Sciences 9, no. 19 (September 28, 2019): 4060. http://dx.doi.org/10.3390/app9194060.

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A novel method for finding linear mappings among word embeddings for several languages, taking as pivot a shared, multilingual embedding space, is proposed in this paper. Previous approaches learned translation matrices between two specific languages, while this method learns translation matrices between a given language and a shared, multilingual space. The system was first trained on bilingual, and later on multilingual corpora as well. In the first case, two different training data were applied: Dinu’s English–Italian benchmark data, and English–Italian translation pairs extracted from the PanLex database. In the second case, only the PanLex database was used. The system performs on English–Italian languages with the best setting significantly better than the baseline system given by Mikolov, and it provides a comparable performance with more sophisticated systems. Exploiting the richness of the PanLex database, the proposed method makes it possible to learn linear mappings among an arbitrary number of languages.

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David, P. "Using Pivot Consistency to Decompose and Solve Functional CSPs." Journal of Artificial Intelligence Research 2 (May 1, 1995): 447–74. http://dx.doi.org/10.1613/jair.167.

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Many studies have been carried out in order to increase thesearch efficiency of constraint satisfaction problems; among them,some make use of structural properties of the constraintnetwork; others take into account semantic properties of theconstraints, generally assuming that all the constraints possessthe given property. In this paper, we propose a new decompositionmethod benefiting from both semantic properties of functional constraints (not bijective constraints) and structuralproperties of the network; furthermore, not all the constraints needto be functional. We show that under some conditions, the existenceof solutions can be guaranteed. We first characterize a particularsubset of the variables, which we name a root set. We thenintroduce pivot consistency, a new local consistency which is aweak form of path consistency and can be achieved in O(n^2d^2)complexity (instead of O(n^3d^3) for path consistency), and wepresent associated properties; in particular, we show that anyconsistent instantiation of the root set can be linearly extended to a solution, which leads to the presentation of the aforementioned new method for solving by decomposing functional CSPs.

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de Albuquerque, Anesmar Olino, Osmar Abílio de Carvalho Júnior, Osmar Luiz Ferreira de Carvalho, Pablo Pozzobon de Bem, Pedro Henrique Guimarães Ferreira, Rebeca dos Santos de Moura, Cristiano Rosa Silva, Roberto Arnaldo Trancoso Gomes, and Renato Fontes Guimarães. "Deep Semantic Segmentation of Center Pivot Irrigation Systems from Remotely Sensed Data." Remote Sensing 12, no. 13 (July 6, 2020): 2159. http://dx.doi.org/10.3390/rs12132159.

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The center pivot irrigation system (CPIS) is a modern irrigation technique widely used in precision agriculture due to its high efficiency in water consumption and low labor compared to traditional irrigation methods. The CPIS is a leader in mechanized irrigation in Brazil, with growth forecast for the coming years. Therefore, the mapping of center pivot areas is a strategic factor for the estimation of agricultural production, ensuring food security, water resources management, and environmental conservation. In this regard, digital processing of satellite images is the primary tool allowing regional and continuous monitoring with low costs and agility. However, the automatic detection of CPIS using remote sensing images remains a challenge, and much research has adopted visual interpretation. Although CPIS presents a consistent circular shape in the landscape, these areas can have a high internal variation with different plantations that vary over time, which is difficult with just the spectral behavior. Deep learning using convolutional neural networks (CNNs) is an emerging approach that provokes a revolution in image segmentation, surpassing traditional methods, and achieving higher accuracy and efficiency. This research aimed to evaluate the use of deep semantic segmentation of CPIS from CNN-based algorithms using Landsat-8 surface reflectance images (seven bands). The developed methodology can be subdivided into the following steps: (a) Definition of three study areas with a high concentration of CPIS in Central Brazil; (b) acquisition of Landsat-8 images considering the seasonal variations of the rain and drought periods; (c) definition of CPIS datasets containing Landsat images and ground truth mask of 256×256 pixels; (d) training using three CNN architectures (U-net, Deep ResUnet, and SharpMask); (e) accuracy analysis; and (f) large image reconstruction using six stride values (8, 16, 32, 64, 128, and 256). The three methods achieved state-of-the-art results with a slight prevalence of U-net over Deep ResUnet and SharpMask (0.96, 0.95, and 0.92 Kappa coefficients, respectively). A novelty in this research was the overlapping pixel analysis in the large image reconstruction. Lower stride values had improvements quantified by the Receiver Operating Characteristic curve (ROC curve) and Kappa, and fewer errors in the frame edges were also perceptible. The overlapping images significantly improved the accuracy and reduced the error present in the edges of the classified frames. Additionally, we obtained greater accuracy results during the beginning of the dry season. The present study enabled the establishment of a database of center pivot images and an adequate methodology for mapping the center pivot in central Brazil.

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Khamayseh, Faisal T. "Inferring Student's Chat Topic in Colloquial Arabic Text using Semantic Representation." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 4 (August 1, 2016): 1897. http://dx.doi.org/10.11591/ijece.v6i4.10403.

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Since the colloquial Arabic is now widespread it is required to describe the collection and classification of a multi-dialectal corpus of Arabic. Nowadays, colloquial multi-dialectal comes in almost country based forms such as Egyptian, Iraqi, Levantine, Tunisian, etc. This paper discusses a new method for analyzing the conversation of the educational chat room using Corpus for Palestinian Arabic and Stanford Tagger. This method represents the key words using semantic net-like representation to obtain the main subjects of the conversation. The main subject of the chat is obtained using the proposed method which shows a high accuracy. Using Arabic Corpus, Stanford Tagger and percentage of words will add more accuracy. The study also examines the effect of pivot distribution based on occurrences and <em>betweeness</em> values of the pivots over the text. This study examines some of the characteristics of the texts written in colloquial Arabic dialect and analyzes the free expressive Arabic statements. The results of the paper show that the core can be determined by combining both the occurrences and the distribution of the word over the conversation.

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Zhang, Yiming, Haozheng Liu, Jiaming Feng, and Xu Zhang. "Innovative Label Embedding for Food Safety Comment Classification: Fusion of Self-Semantic and Self-Knowledge Features." HighTech and Innovation Journal 5, no. 1 (March 1, 2024): 170–84. http://dx.doi.org/10.28991/hij-2024-05-01-013.

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Food safety comment classification represents a specialized task within the realm of text classification. The objective is to efficiently identify a large volume of food safety comments, aiding relevant authorities in timely food analysis and safety alerts. Traditional methods typically employ one-hot encoding for label processing. However, in real-world situations, classified labels often convey valuable semantic information and guidance. This paper introduces an innovative approach to enhance the classification performance of food safety comments by embedding label information. Initially, we extracted generic sentiment pivot words from various classification labels as label description information. Subsequently, we employ a joint embedding approach to integrate this label description information into the text. This process will pool the expressions of the pivot word into the corresponding sentiment labels in the known domains after averaging to get the embedded expression. This aims to acquire highly detailed self-semantic feature vectors and self-knowledge feature vectors that are integrated with labeled descriptive information. Then, feed the semantic representation of comments and the word-embedded representation of labeled description information into a time-step-based multilayer Bi-LSTM and a step-based multilayer CNN, respectively. Ultimately, we concatenate these two feature vectors to facilitate matching, thereby fusing the self-semantic and self-knowledge features of labeled description information to train a classification model for food safety comments. Experimental results on the food safety comment dataset showcase a noteworthy improvement of 1.74% and 1.27% in Macro_Precision and Macro_F1 metrics, respectively, compared to BERT, BERT-RNN, and BERT-CNN. Through extensive ablation experiments and additional studies, our method effectively embeds labeling information, demonstrating a clear advantage over traditional methods in the task of classifying food safety comments. Doi: 10.28991/HIJ-2024-05-01-013 Full Text: PDF

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Izre'el, Shlomo. "The syntax of existential constructions." Journal of Speech Sciences 11 (July 11, 2022): e022001. http://dx.doi.org/10.20396/joss.v11i00.16181.

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This study, in two parts, endeavors a novel analysis of existential constructions, based on a different theoretical setting of clause structure, where the predicate is taken as a necessary and sufficient constituent of the clause. Leaning on this perception, the analyses of existential constructions developed here tries to overcome the discrepancy between form and (semantic and informational) meaning in Hebrew existential constructions. The main part of the study deals with affirmative existential-presentative constructions, used to introduce referents into the discourse. Most of the constructions have been analyzed as consisting of an existential constituent, viewed as a modal marker, and a pivot, regarded as the core component of the predicate domain. This analysis is shown to be valid for both the existential marker jeʃ and for its suppletive verbal forms, derived from √hjj ‘be’. A distinction is made between verbal forms with non-referential and referential verb-bound person markers, where the latter, found with expected, known or given pivots, function as focus marking devices, coming in complementary distribution with prosodic marking of focus. Thus, presentative-existential sentences are formed as unipartite sentences, consisting of only a predicate domain. The last two sections of Part I deal with constructions where the existential constituent follows the pivot and with constructions where the pivot is definite. Part II deals with other existential constructions, including negative constructions; bipartite existential sentences; existential constituents as sole constituents in a sentence; existential constituents with clitic referential markers; and the use of existential markers as interjections or discourse markers.

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Chen, Xinyu, Jiajie Xu, Rui Zhou, Pengpeng Zhao, Chengfei Liu, Junhua Fang, and Lei Zhao. "S2R-tree: a pivot-based indexing structure for semantic-aware spatial keyword search." GeoInformatica 24, no. 1 (July 8, 2019): 3–25. http://dx.doi.org/10.1007/s10707-019-00372-z.

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Dissertations / Theses on the topic "Semantic pivot"

Nikiema, Jean. "Intégration de connaissances biomédicales hétérogènes grâce à un modèle basé sur les ontologies de support." Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0179/document.

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Dans le domaine de la santé, il existe un nombre très important de sources de connaissances, qui vont de simples terminologies, classifications et vocabulaires contrôlés à des représentations très formelles, que sont les ontologies. Cette hétérogénéité des sources de connaissances pose le problème de l’utilisation secondaire des données, et en particulier de l’exploitation de données hétérogènes dans le cadre de la médecine personnalisée ou translationnelle. En effet, les données à utiliser peuvent être codées par des sources de connaissances décrivant la même notion clinique de manière différente ou décrivant des notions distinctes mais complémentaires.Pour répondre au besoin d’utilisation conjointe des sources de connaissances encodant les données de santé, nous avons étudié trois processus permettant de répondre aux conflits sémantiques (difficultés résultant de leur mise en relation) : (1) l’alignement qui consiste à créer des relations de mappings (équivalence et/ou subsumption) entre les entités des sources de connaissances, (2) l’intégration qui consiste à créer des mappings et à organiser les autres entités dans une même structure commune cohérente et, enfin, (3) l’enrichissement sémantique de l’intégration qui consiste à créer des mappings grâce à des relations transversales en plus de celles d’équivalence et de subsumption.Dans un premier travail, nous avons aligné la terminologie d’interface du laboratoire d’analyses du CHU de Bordeaux à la LOINC. Deux étapes principales ont été mises en place : (i) le prétraitement des libellés de la terminologie locale qui comportaient des troncatures et des abréviations, ce qui a permis de réduire les risques de survenue de conflits de nomenclature, (ii) le filtrage basé sur la structure de la LOINC afin de résoudre les différents conflits de confusion.Deuxièmement, nous avons intégré RxNorm à la sous-partie de la SNOMED CT décrivant les connaissances sur les médicaments afin d’alimenter la SNOMED CT avec les entités de RxNorm. Ainsi, les médicaments dans RxNorm ont été décrits en OWL grâce à leurs éléments définitionnels (substance, unité de mesure, dose, etc.). Nous avons ensuite fusionné cette représentation de RxNorm à la structure de la SNOMED CT, résultant en une nouvelle source de connaissances. Nous avons ensuite comparé les équivalences inférées (entre les entités de RxNorm et celles de la SNOMED CT) grâce à cette nouvelle structure avec les équivalences créées de manière morphosyntaxique. Notre méthode a résolu des conflits de nomenclature mais s’est confrontée à certains conflits de confusion et d’échelle, ce qui a mis en évidence le besoin d’améliorer RxNorm et SNOMED CT.Finalement, nous avons réalisé une intégration sémantiquement enrichie de la CIM10 et de la CIMO3 en utilisant la SNOMED CT comme support. La CIM10 décrivant des diagnostics et la CIMO3 décrivant cette notion suivant deux axes différents (celui des lésions histologiques et celui des localisations anatomiques), nous avons utilisé la structure de la SNOMED CT pour retrouver des relations transversales entre les concepts de la CIM10 et de la CIMO3 (résolution de conflits ouverts). Au cours du processus, la structure de la SNOMED CT a également été utilisée pour supprimer les mappings erronés (conflits de nomenclature et de confusion) et désambiguïser les cas de mappings multiples (conflits d’échelle)
In the biomedical domain, there are almost as many knowledge resources in health as there are application fields. These knowledge resources, described according to different representation models and for different contexts of use, raise the problem of complexity of their interoperability, especially for actual public health problematics such as personalized medicine, translational medicine and the secondary use of medical data. Indeed, these knowledge resources may represent the same notion in different ways or represent different but complementary notions.For being able to use knowledge resources jointly, we studied three processes that can overcome semantic conflicts (difficulties encountered when relating distinct knowledge resources): the alignment, the integration and the semantic enrichment of the integration. The alignment consists in creating a set of equivalence or subsumption mappings between entities from knowledge resources. The integration aims not only to find mappings but also to organize all knowledge resources’ entities into a unique and coherent structure. Finally, the semantic enrichment of integration consists in finding all the required mapping relations between entities of distinct knowledge resources (equivalence, subsumption, transversal and, failing that, disjunction relations).In this frame, we firstly realized the alignment of laboratory tests terminologies: LOINC and the local terminology of Bordeaux hospital. We pre-processed the noisy labels of the local terminology to reduce the risk of naming conflicts. Then, we suppressed erroneous mappings (confounding conflicts) using the structure of LOINC.Secondly, we integrated RxNorm to SNOMED CT. We constructed formal definitions for each entity in RxNorm by using their definitional features (active ingredient, strength, dose form, etc.) according to the design patterns proposed by SNOMED CT. We then integrated the constructed definitions into SNOMED CT. The obtained structure was classified and the inferred equivalences generated between RxNorm and SNOMED CT were compared to morphosyntactic mappings. Our process resolved some cases of naming conflicts but was confronted to confounding and scaling conflicts, which highlights the need for improving RxNorm and SNOMED CT.Finally, we performed a semantically enriched integration of ICD-10 and ICD-O3 using SNOMED CT as support. As ICD-10 describes diagnoses and ICD-O3 describes this notion according to two different axes (i.e., histological lesions and anatomical structures), we used the SNOMED CT structure to identify transversal relations between their entities (resolution of open conflicts). During the process, the structure of the SNOMED CT was also used to suppress erroneous mappings (naming and confusion conflicts) and disambiguate multiple mappings (scale conflicts)

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Yamamoto, Shiho. "Recherches sur les relatives à pivot interne en japonais : description syntaxique et questions d'interprétation." Thesis, Paris 3, 2010. http://www.theses.fr/2010PA030048.

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Cette thèse a pour objet l'étude de la syntaxe et de l'interprétation des constructions dites relatives à pivot interne [RPI] en japonais. Le japonais est souvent décrit comme disposant de deux systèmes de relativisation, la relative régulière, prénominale, et la RPI. Reprenant les premiers travaux sur ces constructions, dus à S.-Y. Kuroda, nous montrons que la RPI n'est pas un cas de modification nominale comparable à celui de la relative régulière, mais plutôt un cas de coordination de deux propositions internes à la phrase compète. Nous proposons, sur le plan syntaxique, une analyse de -no comme réalisation phonologique d'un déterminant, D, suivant partiellement les hypothèses générales de Kayne [1994]. Pour l'interprétation de la RPI, nous défendons l'hypothèse selon laquelle elle se comporte comme un topique scénique qui précède les topiques ordinaires, itérables, de Rizzi [1997]. Nous proposons dans un premier temps, la montée en FL de la proposition enchâssée, et dans un second temps, une analyse de la suite de [trace + -no] qui reste in situ comme équivalent du pronom démonstratif sore
This dissertation is a study of the syntax and semantics of the so-called Head-Internal Relative [HIR] clauses in Japanese. This language is generally describe as possessing two distinct relativisation strategies, the unmarked, prenominal, relatives clauses on the one hand, and the HIRs on the other. Returning to the first descriptions of the latter [cf. S-Y. Kuroda 1974, 1975-76], I demonstrate that, semantically, IHR clauses are not a case of adnominal modification; thus, what appears to be a case of [syntactic] embedding is in fact an unexpected case of coordination of two propositions, corresponding to the IHR clause and the main clause. The syntactic analysis of the HIR relies on the idea that -no is a D, borrowing in part from Kayne's [1994] well-known analysis of relative clauses. However, at the semantic interpretation level, we propose that the contents of the HRI is a proposition which functions like a scenic topic which precedes Rizzi's [1997] iterable topic phrases. We are thus led to suggest that the IHR[or its contents] raises to the left periphery, and that the sequence [trace + -no] left behind functions like the demonstrative pronoun sore when it is used anaphorically rather than deictically

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De, Lagane de Malezieux Guillaume. "Contributions à l’ingénierie multilingue et sémantique des exigences en système de systèmes." Electronic Thesis or Diss., Université Grenoble Alpes, 2023. http://www.theses.fr/2023GRALM061.

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Notre recherche concerne le traitement de grosses spécifications dans le domaine des systèmes de systèmes. Un cahier des charges ou une spécification est un ensemble structuré d’exigences. Les outils actuels ne permettent pas de détecter les cas d’inconsistance, d’incomplétude, voire d’incorrection (dus à des ambiguïtés) ou de difficulté de compréhension (due à la complexité des énoncés), qui posent de nombreux problèmes, et peuvent même causer des catastrophes lors de la réalisation puis de la mise en œuvre1. Après avoir fait un état de l’art assez complet sur les systèmes de traitement des exigences (STEX), et sur les domaines qui peuvent participer à leur amélioration, nous proposons une architecture mettant en œuvre des techniques de TALN, d’élicitation interactive du sens, d’extraction de contenu dans une ou plusieurs ontologies, et de calcul sémantique. Une représentation interlingue (graphe UNL) de chaque exigence est obtenue grâce à une analyse multiple factorisante suivie d’une étape de désambiguïsation interactive (DI) reprenant en l’améliorant la technique prototypée dans le projet LIDIA [Blanchon & al. 1994] : repérage des ambiguïtés, calcul automatique d’un arbre de questions, puis mise en œuvre à l’initiative de l’utilisateur, avec une stratégie paramétrable et des interfaces plus ergonomiques (nuages de mots pour les ambiguïtés lexicales, possibilité de manipulation directe pour les ambiguïtés structurelles). Il est alors possible de créer et stocker des annotations visualisables en format auto-explicatif, de sorte que la communication soit à sens garanti.Une fois les graphes UNL corrects obtenus, on procède à l’extraction de contenu, sous forme d’énoncés logiques (en OWL) dans une ontologie cadre et dans une ontologie métier, et à des calculs logiques (inférenciels) pouvant détecter des cas d’incohérence ou d’incomplétude. Un problème récurrent et difficile est la mise en œuvre de solutions de ce type (TALN+IA) sous forme d’ajout aux systèmes déjà lourds de gestion d’ensembles d’exigences (sous DOORS, RQS, ou SBOCS). Pour cela, nous proposons deux environnements. (1) UNSEL-INTER assure la mise en œuvre des ressources et algorithmes de UNSEL-DEVLING et UNSEL-DEVSEM, et du dialogue de désambiguïsation préliminaire à l’extraction, puis de l’interaction éventuelle lancée par UNSEL-SEM lors de la détection d’inconsistances ou d’incomplétudes. (2) UNSEL-OPER est un frontal interagissant avec le contenu d’un STEX, mettant en œuvre les traitements linguistico-sémantiques par appels à UNSEL-INTER, stockant les résultats (graphes UNL, contenu logique extrait, traductions, forme DAE) dans une base de données référant aux exigences du STEX, et notifiant le STEX des reformulations conseillées par UNSEL-SEM. Le prototype UNSEL complet a pu être validé sur une partie de la spécification SSS gérée par SBOCS. Les perspectives sont, outre le passage à l’échelle et l’opérationnalisation dans un cadre industriel, l’adaptation à d’autres applications, telles que la TA interactive de haute qualité, la construction de présentations de textes à sens garanti, et la réponse à des questions ciblées sur de gros documents comme des rapports annuels de sociétés.Ce travail a conduit à l’introduction d’un thème novateur, objet d'une recherche future, la découverte dans un corpus de types d’ambiguïté non encore répertoriés, et de proposition automatique de règles de DI correspondantes
Contributions to the multilingual and semantic engineering of systems of systems requirementsOur research concerns the processing of large specifications in the field of systems of systems. A specification is a structured set of requirements. Current tools do not allow to detect cases of inconsistency, incompleteness, or even ambiguity or difficulty of comprehension, which pose many problems, and can even cause disasters during the realization and then the implementation. After having reviewed the state of the art on requirements processing systems (RPS), we propose an architecture implementing NLP techniques, interactive meaning elicitation, content extraction in one or more ontologies, and semantic computation. A cross-lingual representation (UNL graph) of each requirement is obtained thanks to a multiple factoring analysis followed by an interactive disambiguation (ID) step that improves on the technique prototyped in the LIDIA project [Blanchon & al. 1994]: automatic computation of a question tree, then user-initiated implementation, with a configurable strategy and more ergonomic interfaces (word clouds for lexical ambiguities, direct manipulation possibility for structural ambiguities). At this point, it is possible to create and store annotations that can be visualized in an self-explanatory format.A recurring and difficult problem is the implementation of solutions of this type (NLP + AI) as an addition to the already heavy systems for managing sets of requirements (under DOORS, RQS, or SBOCS). For this, we offer two environments. (1) UNSEL-INTER ensures the implementation of the resources and algorithms of UNSEL-DEVLING and UNSEL-DEVSEM, and of the disambiguation dialogue preliminary to the extraction, then of the possible interaction launched by UNSEL-SEM during the detection inconsistencies or incompleteness. (2) UNSEL-OPER is a front-end interacting with the content of a STEX, implementing linguistic-semantic processing by calls to UNSEL-INTER, storing the results (UNL graphs, extracted logical content, translations, SED form) in a database referring to STEX requirements, and notifying STEX of reformulations recommended by UNSEL-SEM. The complete UNSEL prototype could be validated on part of the SSS specification managed by SBOCS. The prospects are, in addition to scaling up and operationalizing in an industrial setting, the adaptation to other applications, such as high-quality interactive MT, the construction of meaning-guaranteed textual presentations, and answering targeted questions on voluminous documents such as annual company reports. This work has also led to the introduction of an innovative research direction, to be pursued in the future, namely the machine-aided discovery in a corpus of not yet described ambiguity types and the automatic proposal of ID rules

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Oosterman, J. M., H. Hendriks, S. Scott, Kathryn Lord, N. White, and E. L. Sampson. "When Pain Memories Are Lost: A Pilot Study of Semantic Knowledge of Pain in Dementia." 2014. http://hdl.handle.net/10454/10477.

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Objective It has been documented that pain in people with dementia is often under-reported and poorly detected. The reasons for this are not clearly defined. This project aimed to explore semantic concepts of pain in people with dementia and whether this is associated with clinical pain report. Design Cohort study with nested cross-sectional analysis. Setting Acute general hospital medical wards for older people. Subjects People with dementia (N = 26) and control participants (N = 13). Methods Two subtests of semantic memory for pain: 1) Identifying painful situations from a standardized range of pictures; 2) Describing the concept of pain. Participants also indicated whether they were in pain or not, were observed for pain (PAINAD scale) and completed the Wong–Baker FACES scale to indicate pain severity. Results Compared with the control group, people with dementia were less able to identify painful situations and used fewer categories to define their concept of pain. In turn, the performance on these two measures was related to the reported presence and, albeit less strongly, to the reported severity of pain, indicating that a reduction in semantic memory for pain is associated with a decline in reported pain. Conclusions This study is the first to show that semantic memory for pain is diminished in dementia patients. When using clinical pain tools, clinicians should consider these effects which may bias clinical pain ratings when they evaluate and manage pain in these patients. This might improve the recognition and management of pain in people with dementia.
This project is funded jointly by Alzheimer’s Society and the BUPA Foundation (Grant reference number: 131). JMO and ELS are involved in the European COST-Action TD 1005 (Pain Assessment in Patients with Impaired Cognition, especially in Dementia).

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Gardner, Jesse William. "A pilot project exploring the feasibility of enlisting health information & support networks to enable health information seekers, using semantic web middleware." Thesis, 2019. http://hdl.handle.net/1828/11194.

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My Thesis posits a novel method of utilizing emerging web semantics, through HTML5 markup; to improve experience of Health Information seekers through a framework for creating functional, tailored Health Information Resource Collections potentially hosted by their own Health Information Support Networks; and based upon long-standing principles of online Information Retrieval. Most such organizations have websites, with links to useful Resources. This research exemplifies how to design and to present the Resource Collections as pathfinders to existing online Health Information, adding context to each link, to directly address the needs of each community served. The research appeals to a Needs Analysis process rooted in Everyday Life Information Seeking research methodologies, especially Participatory Action Research. As a pilot project, the Needs Analysis focuses necessarily on the Spina Bifida & Hydrocephalus community – with which the author of the Thesis is intimately familiar as a person living with Hydrocephalus, making the choice of a Participatory Action Research framework ideal – and enlisted just one National (Canada) and one Regional (British Columbia) Association for the same rationale. Results of the Needs Analysis were used to identify necessary Resources, but also to select familiar web tools and technologies for design of the Resource Collection and Resource Cards. At completion, there is a functional Collection of Spina Bifida & Hydrocephalus Resources for researchers, caregivers, or patients with Spina Bifida and/or Hydrocephalus – not limited to members of any organization, but best suited by design to the two through which analysis was done.
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VEDROVÁ, Adéla. "Sémantika české pivní reklamy aneb "Chlapi sobě"." Master's thesis, 2019. http://www.nusl.cz/ntk/nusl-398987.

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The thesis focuses on the semantic analysis of the advertisement of different Czech beer brands which have been on the market for the last twenty years. The theoretical part consists of the interpretation of marketing strategies and psychology and decodes the typical advertising language and content of chosen advertisements. The thesis also deals with the history of beer, brewery and law restrictions of advertising alcoholic products.

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Books on the topic "Semantic pivot"

Bárány, András, Oliver Bond, and Irina Nikolaeva, eds. Prominent Internal Possessors. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198812142.001.0001.

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This volume is the first to provide a comprehensive cross-linguistic overview of an understudied typological phenomenon, the clause-level argument-like behaviour of internal possessors. In some languages, adnominal possessors—or a subset thereof—figure more prominently than expected in the phrase-external syntax, by controlling predicate agreement and/or acting as a switch-reference pivot in same-subject relations. There is no independent evidence that such possessors are external to the possessive phrase or that they assume head status within it. This creates a puzzle for virtually all syntactic theories, as it is generally believed that agreement and switch-reference target phrasal heads rather than dependents. Following an introduction to the typology of the phenomenon and an overview of possible syntactic analyses, chapters in the volume offer more focussed case studies from a wide range of languages spoken in the Americas, Eurasia, South Asia, and Australia. The contributions are largely based on novel data collected by the authors and present thorough discussions of the syntactic, semantic, and pragmatic properties of prominent internal possessors in the relevant languages. The volume will be of interest to researchers and students from graduate level upwards in the fields of comparative linguistics, syntax, typology, and semantics.

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Book chapters on the topic "Semantic pivot"

Popov, Igor O., M. C. Schraefel, Wendy Hall, and Nigel Shadbolt. "Connecting the Dots: A Multi-pivot Approach to Data Exploration." In The Semantic Web – ISWC 2011, 553–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25073-6_35.

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Liu, Di, Conghui Zhu, Tiejun Zhao, Xiaoxue Wang, and Muyun Yang. "Pivot-Based Semantic Splicing for Neural Machine Translation." In Communications in Computer and Information Science, 14–24. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3635-4_2.

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Steiner-Khamsi, Gita. "What Is in a Reference? Theoretically Understanding the Uses of Evidence in Education Policy." In Evidence and Expertise in Nordic Education Policy, 33–57. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-91959-7_2.

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AbstractThe chapter deals with the reference—the unit of analysis for our bibliometric analyses—and examines what it stands for in the policy process. We found Paul Cairney’s (The Politics of Evidence-Based Policymaking. Palgrave Pivot, 2015) definition useful: “‘[e]vidence’ is assertion backed by information.” In concert with Cairney’s definition, we treat references as a construct or an aggregate of several pieces of information (authorship, year of publication, topic or theme, etc.) that helps position the author in a larger semantic space. We have used all these constitutive elements as epistemological cues for understanding not only whose texts or whose knowledge the authors have selected to substantiate their points with, but also whose knowledge they cite as sources of expertise in order to reduce uncertainty, enhance credibility, or generate legitimacy about the validity of their own claims or assertions. In an era in which we have a surplus of information as well as a surplus of evidence, this is no small enterprise.

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Navigli, Roberto, Riccardo Orlando, Cesare Campagnano, and Simone Conia. "Universal Semantic Annotator." In European Language Grid, 349–54. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17258-8_28.

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AbstractExplicit semantic knowledge has often been considered a necessary ingredient to enable the development of intelligent systems. However, current stateof- the-art tools for the automatic extraction of such knowledge often require expert understanding of the complex techniques used in lexical and sentence-level semantics and their linguistic theories. To overcome this limitation and lower the barrier to entry, we present the Universal Semantic Annotator (USeA) ELG pilot project, which offers a transparent way to automatically provide high-quality semantic annotations in 100 languages through state-of-the-art models, making it easy to exploit semantic knowledge in real-world applications.

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Kuroda, S. Y. "Pivot-Independent Relativization in Japanese." In Japanese Syntax and Semantics, 114–74. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2789-9_4.

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Workman, Michael. "Using Symbols for Semantic Representations: A Pilot Study of Clinician Opinions of a Web 3.0 Medical Application." In Semantic Web, 31–38. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16658-2_3.

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Guasch, Cecile, Giorgia Lodi, and Sander Van Dooren. "Semantic Knowledge Graphs for Distributed Data Spaces: The Public Procurement Pilot Experience." In The Semantic Web – ISWC 2022, 753–69. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-19433-7_43.

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Koeva, Svetla. "Multilingual Image Corpus." In European Language Grid, 313–18. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17258-8_22.

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AbstractThe ELG pilot project Multilingual Image Corpus (MIC 21) provides a large image dataset with annotated objects and multilingual descriptions in 25 languages. Our main contributions are: the provision of a large collection of highquality, copyright-free images; the formulation of an ontology of visual objects based on WordNet noun hierarchies; precise manual correction of automatic image segmentation and annotation of object classes; and association of objects and images with extended multilingual descriptions. The dataset is designed for image classification, object detection and semantic segmentation. It can be also used for multilingual image caption generation, image-to-text alignment and automatic question answering for images and videos.

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Stegmeier, Jörn, Jakob Hartig, Michaela Leštáková, Kevin Logan, Sabine Bartsch, Andrea Rapp, and Peter F. Pelz. "Development of an Annotation Schema for the Identification of Semantic Uncertainty in DIN Standards." In Lecture Notes in Mechanical Engineering, 23–34. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77256-7_3.

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AbstractThis paper presents the results of a pilot study carried out in cooperation between Linguistics and Mechanical Engineering, funded by the collaborative research centre (CRC) 805 “Beherrschung von Unsicherheit in lasttragenden Systemen des Maschinenbaus”. Our goal is to help improve norm compliant product development and engineering design by focusing on ambiguous language use in norm texts (= “semantic uncertainty”). Depending on the country and product under development, industry standards may be legally binding. Thus, standards play a vital role in reducing uncertainty for manufacturers and engineers by providing requirements for product development and engineering design. However, uncertainty is introduced by the standards themselves in various forms, the most notable of which are the use of underspecified concepts, modal verbs like should, and references to texts which contain semantically uncertain parts. If conformity to standards is to be ensured, the person using the standards must interpret them and document the interpretation. In order to support users in these tasks, we developed an annotation schema which allows the identification and classification of semantically uncertain segments of standards, used the schema to create a taxonomy of semantic uncertainty in standards, developed a proof-of-concept information system. The results of this project can be used as a starting point for automated annotation. The information system alerts users to semantically uncertain segments of standards, provides background information, and allows them to document their decisions how to handle the semantically uncertain parts.

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Xue, F., K. Chen, D. Liu, Y. Niu, and W. S. Lu. "An Optimization-Based Semantic Building Model Generation Method with a Pilot Case of a Demolished Construction." In Proceedings of the 21st International Symposium on Advancement of Construction Management and Real Estate, 231–41. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6190-5_22.

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Conference papers on the topic "Semantic pivot"

Trieu, Hai-Long, and Le-Minh Nguyen. "Applying Semantic Similarity to Phrase Pivot Translation." In 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2016. http://dx.doi.org/10.1109/ictai.2016.0160.

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Li, Tian, Xiang Chen, Zhen Dong, Kurt Keutzer, and Shanghang Zhang. "Domain-Adaptive Text Classification with Structured Knowledge from Unlabeled Data." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/585.

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Domain adaptive text classification is a challenging problem for the large-scale pretrained language models because they often require expensive additional labeled data to adapt to new domains. Existing works usually fails to leverage the implicit relationships among words across domains. In this paper, we propose a novel method, called Domain Adaptation with Structured Knowledge (DASK), to enhance domain adaptation by exploiting word-level semantic relationships. DASK first builds a knowledge graph to capture the relationship between pivot terms (domain-independent words) and non-pivot terms in the target domain. Then during training, DASK injects pivot-related knowledge graph information into source domain texts. For the downstream task, these knowledge-injected texts are fed into a BERT variant capable of processing knowledge-injected textual data. Thanks to the knowledge injection, our model learns domain-invariant features for non-pivots according to their relationships with pivots. DASK ensures the pivots to have domain-invariant behaviors by dynamically inferring via the polarity scores of candidate pivots during training with pseudo-labels. We validate DASK on a wide range of cross-domain sentiment classification tasks and observe up to 2.9% absolute performance improvement over baselines for 20 different domain pairs. Code is available at https://github.com/hikaru-nara/DASK.

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Yang, Jian, Yuwei Yin, Shuming Ma, Dongdong Zhang, Shuangzhi Wu, Hongcheng Guo, Zhoujun Li, and Furu Wei. "UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine Translation." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/618.

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Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable. Multilingual neural machine translation (MNMT) enables one-pass translation using shared semantic space for all languages compared to the two-pass pivot translation but often underperforms the pivot-based method. In this paper, we propose a novel method, named as Unified Multilingual Multiple teacher-student Model for NMT (UM4). Our method unifies source-teacher, target-teacher, and pivot-teacher models to guide the student model for the zero-resource translation. The source teacher and target teacher force the student to learn the direct source-target translation by the distilled knowledge on both source and target sides. The monolingual corpus is further leveraged by the pivot-teacher model to enhance the student model. Experimental results demonstrate that our model of 72 directions significantly outperforms previous methods on the WMT benchmark.

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Petrova, Maria, Maria Ponomareva, and Alexandra Ivoylova. "The Pilot Corpus of the English Semantic Sketches." In Dialogue. RSUH, 2022. http://dx.doi.org/10.28995/2075-7182-2022-21-436-446.

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The paper is devoted to the creation of the semantic sketches for English verbs. The pilot corpus consists of the English-Russian sketch pairs and is aimed to show what kind of contrastive studies the sketches help to conduct. Special attention is paid to the cross-language differences between the sketches with similar semantics. Moreover, we discuss the process of building a semantic sketch, and analyse the mistakes that could give insight to the linguistic nature of sketches.

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Watkins, David, Guillermo Gallardo, and Savio Chau. "Pilot Support System: A Machine Learning Approach." In 2018 IEEE 12th International Conference on Semantic Computing (ICSC). IEEE, 2018. http://dx.doi.org/10.1109/icsc.2018.00067.

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Min, Qingkai, Yuefeng Shi, and Yue Zhang. "A Pilot Study for Chinese SQL Semantic Parsing." In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-1377.

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Biagetti, Erica, Luca Brigada Villa, Chiara Zanchi, and Silvia Luraghi. "Enhancing the semantic and conceptual description of Ancient Greek verbs in WordNet with VerbNet and FrameNet: a treebank-based study." In INTERNATIONAL CONFERENCE on Computational Linguistics and Intellectual Technologies. RSUH, 2023. http://dx.doi.org/10.28995/2075-7182-2023-22-1009-1020.

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This paper presents a pilot study intended to enhance the semantic and conceptual description of Ancient Greek verbs in WordNet with information from two other resources, VerbNet and FrameNet, and to enrich a treebank of Ancient Greek texts with semantic information extracted from the three resources. We provided semantic annotation for verbs based on their morphosyntactic behavior, and performed a number of queries in order to extract occurrences from the Ancient Greek treebank that intended to match the different meanings of each verb. The manual check of the data extracted shows that, in spite of a limited number of mismatches, our queries yielded reliable results. The queries can be further refined in the future and complemented with a rule-based algorithm to map frame elements to dependency structure.

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Mora-Arciniegas, Maria-Belen, Nelson Piedra, and Gladys-Alicia Tenesaca-Luna. "Semantic representation of teaching planning, pilot experience at UTPL." In 2017 IEEE 37th Central America and Panama Convention (CONCAPAN XXXVII). IEEE, 2017. http://dx.doi.org/10.1109/concapan.2017.8278534.

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Ahmadiyah, Adhatus S., Siti Rochimah, and Daniel Siahaan. "Semantic Software Traceability Using Property Listing Task: Pilot Study." In 2022 International Electronics Symposium (IES). IEEE, 2022. http://dx.doi.org/10.1109/ies55876.2022.9888365.

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Agirre, Eneko, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, et al. "SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability." In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015). Stroudsburg, PA, USA: Association for Computational Linguistics, 2015. http://dx.doi.org/10.18653/v1/s15-2045.

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Reports on the topic "Semantic pivot"

Haylock, Stuart. SemaFoRe: Semantic Feature and Repetition therapy in aphasia: A pilot RCT. National Institute for Health and Care Research (NIHR), May 2022. http://dx.doi.org/10.3310/nihropenres.1115186.1.

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Academic literature on the topic 'Semantic pivot'

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Reports on the topic "Semantic pivot"