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Chapitre D'ouvrage Année : 2014

Semantic Facets for Scientific Information Retrieval

Résumé

We present an Information Retrieval System for scientific publications that provides the possibility to filter results according to semantic facets. We use sentence-level semantic annotations that identify specific semantic relations in texts, such as methods, definitions, hypotheses, that correspond to common information needs related to scientific literature. The semantic annotations are obtained using a rule-based method that identifies linguistic clues organized into a linguistic ontology. The system is implemented using Solr Search Server and offers efficient search and navigation in scientific papers.
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Dates et versions

hal-01771488 , version 1 (19-04-2018)

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Iana Atanassova, Marc Bertin. Semantic Facets for Scientific Information Retrieval. Valentina Presutti; Milan Stankovic; Erik Cambria; Iván Cantador; Angelo Di Iorio; Tommaso Di Noia; Christoph Lange; Diego Reforgiato Recupero; Anna Tordai. Semantic Web Evaluation Challenge. SemWebEval 2014, 475, Springer, pp.108-113, 2014, Communications in Computer and Information Science, 978-3-319-12023-2. ⟨10.1007/978-3-319-12024-9_14⟩. ⟨hal-01771488⟩
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