Work place: Univ Pau & Pays Adour / E2S UPPA, Laboratoire d'Informatique de l'Université de Pau et des Pays de l'Adour, EA 3000, 64000 Pau, France
E-mail: Annig.lacayrelle@univ-pau.fr
Website:
Research Interests: Geographic Information System, Information Retrieval, Multimedia Information System
Biography
Dr. Annig Le Parc Lacayrelle is an associate professor at the University of Pau and Pays Adour, Pau, France. She received his Ph.D. degree in 1997 at the Toulouse III University. Her current research concerns, on the one hand, the automatic extraction and indexation of geographical information contained in textual documents and, on the other hand, information retrieval in the indexes obtained.
By Armel Fotsoh Christian Sallaberry Annig Le Parc Lacayrelle
DOI: https://doi.org/10.5815/ijitcs.2019.11.01, Pub. Date: 8 Nov. 2019
As part of the Cognisearch project, we developed a general architecture dedicated to extracting, indexing and searching for complex Named Entities (NEs) in webpages. We consider complex NEs as NEs represented by a list of properties that can be single values (text, number, etc.), "elementary" NEs and/or other complex NEs. Before the indexing of a new extracted complex NE, it is important to make sure that it is not already indexed. Indeed, the same NE may be referenced on several different web platforms. Therefore, we need to be able to establish similarity to consolidate information related to similar complex NEs. This is the focus of this paper. Two issues mainly arise in the computation of similarity between complex NEs: (i) the same property may be expressed differently in the compared NEs; (ii) some properties may be missing. We propose several generic similarity computation approaches that target any type of complex NEs. The two issues outlined above are tackled in these proposals. We experiment and evaluate these approaches with two examples of complex NEs related to the domain of social events.
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