Improving the effectiveness of information retrieval with local context analysis
ACM Transactions on Information Systems (TOIS)
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A review of relevance feedback experiments at the 2003 reliable information access (RIA) workshop.
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A framework for selective query expansion
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Poison pills: harmful relevant documents in feedback
Proceedings of the 14th ACM international conference on Information and knowledge management
Term distillation in patent retrieval
PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20
Enhancing patent retrieval by citation analysis
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Transforming patents into prior-art queries
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
PRES: a score metric for evaluating recall-oriented information retrieval applications
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Exploring structured documents and query formulation techniques for patent retrieval
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Simple vs. sophisticated approaches for patent prior-art search
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Utilizing sub-topical structure of documents for information retrieval
Proceedings of the 4th workshop on Workshop for Ph.D. students in information & knowledge management
Automatic refinement of patent queries using concept importance predictors
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Learning-Based pseudo-relevance feedback for patent retrieval
IRFC'12 Proceedings of the 5th conference on Multidisciplinary Information Retrieval
Leveraging conceptual lexicon: query disambiguation using proximity information for patent retrieval
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
CV-PCR: a context-guided value-driven framework for patent citation recommendation
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Queries in patent prior art search are full patent applications and 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 ambiguous terms in these massive queries. Reducing patent queries by extracting 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 IR 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, hypothesising that removal of these segments can increase the precision of retrieval, while still retaining the useful context to achieve high recall. 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).