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Patent query reduction using pseudo relevance feedback

Ganguly, Debasis and Leveling, Johannes and Magdy, Walid and Jones, Gareth J.F. (2011) Patent query reduction using pseudo relevance feedback. In: 20th ACM Conference on Information and Knowledge Management (CIKM 2011), 24-28 Oct 2011, Glasgow, Scotland.

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Queries in patent prior art search, being full patent applications, are very much longer than standard ad hoc search and web search topics. Standard information retrieval (IR) techniques are not entirely effective for patent prior art search because of the presence of ambiguous terms in these massive queries. Reducing patent queries by extracting small numbers of key terms has been shown to be ineffective mainly because it is not clear what the focus of the query is. An optimal query reduction algorithm must thus seek to retain the useful terms for retrieval favouring recall of relevant patents, but remove terms which impair retrieval effectiveness. We propose a new query reduction technique decomposing a patent application into constituent text segments and computing the Language Modeling (LM) similarities by calculating the probability of generating each segment from the top ranked documents. We reduce a patent query by removing the least similar segments from the query, hypothesizing that removal of segments most dissimilar to the pseudo-relevant documents can increase the precision of retrieval by removing nonuseful context, while still retaining the useful context to achieve high recall as well. Experiments on the patent prior art search collection CLEF-IP 2010, show that the proposed method outperforms standard pseudo relevance feedback (PRF) and a naive method of query reduction based on removal of unit frequency terms (UFTs).

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Query Reduction; Patent Search; Pseudo-Relevance Feedback
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Copyright Information:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:16514
Deposited On:27 Oct 2011 11:01 by Shane Harper. Last Modified 23 Feb 2017 09:39

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