Retrieval of Complex Named Entities on the Web: Proposals for Similarity Computation

Автор: Armel Fotsoh, Christian Sallaberry, Annig Le Parc Lacayrelle

Журнал: International Journal of Information Technology and Computer Science @ijitcs

Статья в выпуске: 11 Vol. 11, 2019 года.

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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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Complex Named Entities, Similarity Computation, Machine Learning, Web Mining

Короткий адрес: https://sciup.org/15017082

IDR: 15017082 | DOI: 10.5815/ijitcs.2019.11.01

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