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Acquiring Lexical Knowledge from Query Logs for Query Expansion in Patent Searching

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2 Author(s)
Tannebaum, W. ; Inst. of Software Technol. & Interactive Syst., Vienna Univ. of Technol., Vienna, Austria ; Rauber, A.

Query expansion is a crucial step in recall-oriented domains such as Patent Searching. Currently, automatic query expansion in patent search is mostly based on statistical measures. Additional query terms are extracted from the query documents based on entropy measures. To automate query expansion in patent searching, we acquire lexical knowledge from Query Logs of USPTO Patent Examiners. Results show good performance in query expansion and patent searching using the lexical database. This will help improving (semi-) automated query expansion in patent searching.

Published in:

Semantic Computing (ICSC), 2012 IEEE Sixth International Conference on

Date of Conference:

19-21 Sept. 2012