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Towards combined semantic and lexical scores based on a new representation of textual data to extract experimental data from scientific publications
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In: ISSN: 1751-5858 ; EISSN: 1751-5866 ; International Journal of Intelligent Information and Database Systems ; https://hal.inrae.fr/hal-03616243 ; International Journal of Intelligent Information and Database Systems, Inderscience, 2022, 15 (1), pp.78. ⟨10.1504/IJIIDS.2022.120146⟩ (2022)
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Combinaison de mesures lexicales et sémantiques pour l'extraction de données expérimentales dans des articlesscientifiques
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In: Extraction et gestion des connaissances - EGC 2021 ; https://hal.archives-ouvertes.fr/hal-03313686 ; Extraction et gestion des connaissances - EGC 2021, Jan 2021, Montpellier, France. pp.501-502 (2021)
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Xart: Discovery of correlated arguments of n-ary relations in text
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In: ISSN: 0957-4174 ; Expert Systems with Applications ; https://hal-agroparistech.archives-ouvertes.fr/hal-01508801 ; Expert Systems with Applications, Elsevier, 2017, 73, pp.115-124. ⟨10.1016/j.eswa.2016.12.028⟩ (2017)
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Xart system: discovering and extracting correlated arguments of n-ary relations from text
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In: 6th International Conference on Web Intelligence, Mining and Semantics (WIMS) ; https://hal-agroparistech.archives-ouvertes.fr/hal-01357738 ; 6th International Conference on Web Intelligence, Mining and Semantics (WIMS), Jun 2016, Nimes, France. pp.8:1-8:12, ⟨10.1145/2912845.2912855⟩ (2016)
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Abstract:
International audience ; In this paper, we present Xart system based on a hybrid method using data mining approaches and syntactic analysis to automatically discover and extract relevant information modeled as n-ary relations from text. A n-ary relation links a studied object with its features considered as several arguments. Our work focuses on extracting quantitative arguments associated with their attributes, i.e. a numerical value and a unit of measure, in order to populate a domain Ontological and Terminological Resource (OTR) with new instances. The proposed method relies on the discovery of correlated arguments in text using sequential pattern mining and the OTR. Then, those Ontological Sequential Patterns (OSP) are enriched with specific syntactic relations in order to construct Ontological Linguistic Sequential Patterns (OLSP) where the arguments are expressed according to different levels of term abstraction (term, grammatical category and concept). We have made concluding experiments on a corpus from food packaging domain where relevant data to be extracted are experimental results on packagings. We have been able to extract up to 4 correlated arguments with a F-measure from 0.6 to 0.8.
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Keyword:
[INFO]Computer Science [cs]
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URL: https://hal-agroparistech.archives-ouvertes.fr/hal-01357738
https://doi.org/10.1145/2912845.2912855
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Découverte et extraction d'arguments de relations n-aires corrélés dans les textes
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In: ISSN: 1764-1667 ; Revue des Nouvelles Technologies de l'Information ; https://hal-agroparistech.archives-ouvertes.fr/hal-01357720 ; Revue des Nouvelles Technologies de l'Information, Editions RNTI, 2016, Fouille de Données Complexes, RNTI-E-31, pp.37-56 ; http://editions-rnti.fr/?procid=100167 (2016)
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An Ontological and Terminological Resource for n-ary Relation Annotation in Web Data Tables
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In: Lecture Notes in Computer Science ; ODBASE'2011: 10th International Conference on Ontologies, DataBases, and Applications of Semantics ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-00616241 ; ODBASE'2011: 10th International Conference on Ontologies, DataBases, and Applications of Semantics, Oct 2011, Crete, Greece. pp.662-679, ⟨10.1007/978-3-642-25106-1_19⟩ ; http://www.onthemove-conferences.org/index.php/odbase11 (2011)
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