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论文类型： 期刊论文

发表时间： 2012-07-01

发表刊物： Journal of Computational Information Systems

收录刊物： EI、Scopus

卷号： 8

期号： 13

页面范围： 5607-5614

ISSN号： 15539105

摘要： Query expansion technologies are widely used in many information retrieval tasks. Most existing approaches are based on the assumption that the most informative terms can be select from top-retrieved documents in the document context level. However, the query expansion methods for general tasks tend not to be optimal choice for special tasks, such as patent search. In the patent articles, the same word from different context fields may be of different importance for retrieval, since the fields, e.g., title and abstracts, describe the patent from various aspects. So these fields may be used to weight the expansion terms more accurately. In this work, we explore the possibility and potential of text fields to extract more effective expansion terms. In particular, we propose a two-stage ranking approach for query expansion based on document fields. First we select top-retrieved documents by BM25F; second, we explore how to weight the different fields based on their importance to improve the term ranking method for effective expansion terms. Experimental results on three TREC test collections show that the patent retrieval performance can be improved when the term ranking method based on fields is used. ? 2011 by Binary Information Press.