Term Similarity-Based Query Expansion for Cross-Language Information Retrieval

Abstract

We propose a query expansion technique which is based on a statistical similarity measure among terms to improve the effectiveness of the dictionary-based cross-language information retrieval (CLIR) method. We employ a term similarity-based sense disambiguation technique proposed in our earlier work to enhance the accuracy of the dictionary-based query translation method. The query expansion technique is then applied to the translation of queries to further improve their retrieval performance. We demonstrate the effectiveness of the two techniques combined using queries in three languages, namely, German, Spanish, and Indonesian, to retrieve English documents from a standard TREC (Text Retrieval Conference) collection. The results of our experiments indicate that the term similarity-based techniques work better when there are more phrases in the queries. In addition, our results also re-emphasize other researchers’ finding that phrase recognition and translation are critical to CLIR’s effectiveness.