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Preliminary Ideas on Concept to Query Closeness Metrics

Authors:
Alejandra Andrea Segura Navarrete
Claudia Martinez A.
Christian Vidal-Castro
Salvador Sánchez-Alonso

Keywords: Ontology; Semantic Web; Web Information Retrieval

Abstract:
The usefulness of knowledge models for information retrieval tasks such as digital resource tagging, query expansion, and recommending, among others, requires that the query concept be present in the model, i.e., exists matching. If the query concept is absent in the ontology, exists matching problem. In this case, it can be identified in the model other sematic and syntactically closeness concepts to the query concept. Once identified the closest concept is possible to extract relevant knowledge from the ontology. The goal of this work is to propose a solution to the problem mentioned, by identifying those variables that can affect the closeness between a query and concepts in a domain ontology. Using these variables as a starting point, we propose 6 indexes for measuring the degree of closeness. We present the results of implementing a search-selection algorithm using indexes based on exact words, contained words, coincidences in descriptive fields, new words and approximate depth. These indices are validated via a case study, and, from these results, we recommend adjustments needed for building a global concept closeness index in future works.

Pages: 73 to 79

Copyright: Copyright (c) IARIA, 2012

Publication date: May 27, 2012

Published in: conference

ISSN: 2308-3972

ISBN: 978-1-61208-200-4

Location: Stuttgart, Germany

Dates: from May 27, 2012 to June 1, 2012