Semantic Filtering of Scientific Articles guided by a Domain Ontology

Fabrice Jouanot (1) , Cyril Labbé (1) , Elena Michael (1) , Marie-Christine Rousset (1) , Maïté Tauber (2) , Federico Ulliana (3)

1 LIG - Laboratoire d'Informatique de Grenoble
2 Centre d'Endocrinologie, Maladies Osseuses, Génétique et Gynécologie Médicale
3 IMAGINE - Intuitive Modeling and Animation for Interactive Graphics & Narrative Environments

The problem that we address in this paper is how to improve the accuracy of retrieving specialized information within a textual scientific corpus. We present a new approach in which the keywords expressing the bibliographical needs of a researcher are related to a domain ontology. We illustrate how such a declarative ontolology-based approach can be used both for computing varied statistics, and also for helping experts to find useful fine-grained information within a textual corpus.

Keywords: semantic search; ontology-based data access; information integration; concept extraction from text

Domains: Information Retrieval [cs.IR]; Artificial Intelligence [cs.AI]

Fabrice Jouanot, Cyril Labbé, Elena Michael, Marie-Christine Rousset, Maïté Tauber, et al.. Semantic Filtering of Scientific Articles guided by a Domain Ontology. WCECS 2014 - World Congress on Engineering and Computer Science 2014, International Association of Engineers, Oct 2014, San Francisco, United States. pp.803-808. ⟨hal-01088092⟩