Pseudo relevance feedback method based on taylor expansion of retrieval function in NTCIR-3 patent retrieval task

Authors:
Kazuaki Kishida
Affiliations:
Surugadai University, Saitama, Japan
Venue:
PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20
Year:
2003

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Pseudo relevance feedback method based on taylor expansion of retrieval function in NTCIR-3 patent retrieval task

PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20

Pseudo relevance feedback method based on taylor expansion of retrieval function in NTCIR-3 patent retrieval task

PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20

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Abstract

Pseudo relevance feedback is empirically known as a useful method for enhancing retrieval performance. For example, we can apply the Rocchio method, which is well-known relevance feedback method, to the results of an initial search by assuming that the top-ranked documents are relevant. In this paper, for searching the NTCIR-3 patent test collection through pseudo feedback, we employ two relevance feedback mechanism; (1) the Rocchio method, and (2) a new method that is based on Taylor formula of linear search functions. The test collection consists of near 700,000 records including full text of Japanese patent materials. Unfortunately, effectiveness of our pseudo feedback methods was not empirically observed at all in the experiment.