2009 | OriginalPaper | Buchkapitel
A Logical Inference Approach to Query Expansion with Social Tags
verfasst von : Christina Lioma, Roi Blanco, Marie-Francine Moens
Erschienen in: Advances in Information Retrieval Theory
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Query Expansion (QE) refers to the Information Retrieval (IR) technique of adding assumed relevant terms to a query in order to render it more informative, and hence more likely to retrieve relevant documents. A key problem is how to identify the terms to be added, and how to integrate them into the original query. We address this problem by using as expansion terms social tags that are freely available on the Web. We integrate these tags into the query by treating the QE process as a logical inference (initially proposed in [3]) and by considering the addition of tags as an extra deduction to this process. This work extends Nie’s logical inference formalisation of QE to process social tags, and proposes an estimation of tag salience, which is experimentally shown to yield competitive retrieval performance.