Pattern-based approaches to semantic relation extraction: A state-of-the-art

Auger, Alain; Barrière, Caroline

doi:10.1075/bct.23.01aug

Cited by 15 publications

(16 citation statements)

References 6 publications

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“…A sample of 100 abstracts was extracted and instances of explicit semantic relations were discovered and manually annotated on these data. Pattern-based approaches of relationship extraction [1] and classification [18] rely on the hypothesis that the context of occurrence of entity mention pairs is characteristic of the semantic relation between the two concepts. Thus, only linguistically explicit relations were taken into account.…”

Section: Semantic Relations In Scientific Literaturementioning

confidence: 99%

A Typology of Semantic Relations Dedicated to Scientific Literature Analysis

Gábor

Zargayouna

Buscaldi

et al. 2016

Semantics, Analytics, Visualization. Enhancing Scholarly Data

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Section: Semantic Relations In Scientific Literaturementioning

confidence: 99%

A Typology of Semantic Relations Dedicated to Scientific Literature Analysis

Gábor

Zargayouna

Buscaldi

et al. 2016

Semantics, Analytics, Visualization. Enhancing Scholarly Data

View full text Add to dashboard Cite

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“…Relation extraction techniques (Grefenstette, 1994) include statistics (looking for repeated segments or meaningful predicate argument structures (Hindle, 1990)), robust or shallow linguistic analyses (mainly pattern matching on syntactically tagged corpora) (Giuliano, Lavelli and Romano, 2006) and learning (to learn new patterns from tagged corpora) (Nédellec and Nazarenko, 2003). A recent state-of-the-art on pattern-based relation extraction from text (Auger and Barriere, 2008) shows that a pattern may correspond to very different characterizations of how a semantic relation may be expressed in a given language and corpora. A pattern defines a way to explore a sequence of words, lemmas, POS, syntactical relations, or semantic classes.…”

Section: Discussionmentioning

confidence: 99%

Ontology Learning by Analyzing XML Document Structure and Content

Aussenac-Gilles

Kamel

2009

Proceedings of the International Conference on Knowledge Engineering and Ontology Development

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Keywords:Natural language processing for ontology learning, extraction of semantic relations, information extraction from structured documents.Abstract: Most existing methods for ontology learning from textual documents rely on natural language analysis. We extend these approaches by taking into account the document structure which bears additional knowledge. The documents that we deal with are XML specifications of databases. In addition to classical linguistic clues, the structural organization of such documents also contributes to convey meaning. In a first stage, we characterize the semantics of XML mark-up and of their relations. Then parsing rules are defined to exploit the XML structure of documents and to create ontology concepts and semantic relations. These rules make it possible to automatically learn a kernel of ontology from documents. In a second stage; this ontology is enriched with the results of text analysis by lexico-syntactic patterns. Both ontology learning rules and patterns are implemented in the Gate platform.

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“…Nous avons aussi choisi d'utiliser des patrons lexico-syntaxiques pour repérer de nouveaux concepts et des relations sémantiques dans les parties du document en texte libre (Auger et al, 2008). Un patron lexico-syntaxique décrit une expression régulière, formée de mots, de catégories grammaticales ou sémantiques, et de symboles, visant à identifier des fragments de texte répondant à ce format.…”

Section: Analyse Du Texte Libreunclassified

Analyses linguistiques et techniques d’alignement pour créer et enrichir une ontologie topographique

Mustière¹,

Abadie²,

Gilles³

et al. 2011

Revue internationale de géomatique

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Dans cet article, nous présentons le projet GéOnto dont un des buts est de construire une ontologie de concepts topographiques. Cette ontologie est réalisée par enrichissement d'une première taxonomie de termes réalisée précédemment, et ce grâce à l'analyse de deux types de documents textuels : des spécifications techniques de bases de données et des récits de voyage. Cet enrichissement s'appuie sur des techniques automatiques de traitement du langage et d'alignement d'ontologies, ainsi que sur des connaissances externes comme des dictionnaires et des bases de toponymes. ABSTRACT. One of the goals of the GéOnto project is to build an ontology of topographic concepts. This ontology results from the enrichment of a first taxonomy developed beforehand, through the analysis of two types of textual documents: technical database specifications and description of journeys. This work relies on natural language processing and ontology alignment techniques, as well as external knowledge resources such as dictionaries and gazetteers.

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Pattern-based approaches to semantic relation extraction: A state-of-the-art

Cited by 15 publications

References 6 publications

A Typology of Semantic Relations Dedicated to Scientific Literature Analysis

A Typology of Semantic Relations Dedicated to Scientific Literature Analysis

Ontology Learning by Analyzing XML Document Structure and Content

Analyses linguistiques et techniques d’alignement pour créer et enrichir une ontologie topographique

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