TY - GEN
T1 - A Logical Inference Approach to Query Expansion with Social Tags
AU - Lioma, Christina
AU - Blanco, Roi
AU - Moens, Marie-Francine
N1 - Published in:
· Proceeding
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Pages 358 - 361
Springer-Verlag Berlin, Heidelberg ©2009
ISBN: 978-3-642-04416-8 doi>10.1007/978-3-642-04417-5_39
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
M3 - Article in proceedings
SP - 358
EP - 361
BT - ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
ER -