Improving Retrieval Results with Discipline-Specific Query Expansion
Choosing the right terms to describe an information need is becoming more difficult as the amount of available information increases. Search-Term-Recommendation (STR) systems can help to overcome these problems. This paper evaluates the benefits that may be gained from the use of STRs in Query Expansion (QE). We create 17 STRs, 16 based on specific disciplines and one giving general recommendations, and compare the retrieval performance of these STRs. The main findings are: (1) QE with specific STRs leads to significantly better results than QE with a general STR, (2) QE with specific STRs selected by a heuristic mechanism of topic classification leads to better results than the general STR, however (3) selecting the best matching specific STR in an automatic way is a major challenge of this process.
KeywordsTerm Suggestion Information Retrieval Thesaurus Query Expansion Digital Libraries Search Term Recommendation
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- 2.Hargittai, E.: Hurdles to information seeking: Spelling and typographical mistakes during users’ online behavior. Journal of the Association of Information Systems 7(1), 52–67 (2006)Google Scholar
- 6.Petras, V.: How one word can make all the difference - using subject metadata for auto-matic query expansion and reformulation. In: Working Notes for the CLEF 2005 Workshop, Vienna, Austria, September 21-23 (2005)Google Scholar
- 7.Petras, V.: Translating Dialects in Search: Mapping between Specialized Languages of Discourse and Documentary Languages. University of California (2006)Google Scholar