A robust retrieval engine for proximal and structural search

Authors:
Katsuya Masuda;Takashi Ninomiya;Yusuke Miyao;Tomoko Ohta;Jun'ichi Tsujii
Affiliations:
University of Tokyo, Bunkyo-ku, Tokyo, Japan;University of Tokyo, Bunkyo-ku, Tokyo, Japan;University of Tokyo, Bunkyo-ku, Tokyo, Japan;University of Tokyo, Bunkyo-ku, Tokyo, Japan;University of Tokyo, Bunkyo-ku, Tokyo, Japan
Venue:
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Year:
2003

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Abstract

In the text retrieval area including XML and Region Algebra, many researchers pursued models for specifying what kinds of information should appear in specified structural positions and linear positions (Chinenyanga and Kushmerick, 2001; Wolff et al., 1999; Theobald and Weilkum, 2000; Clarke et al., 1995). The models attracted many researchers because they are considered to be basic frameworks for retrieving or extracting complex information like events. However, unlike IR by keyword-based search, their models are not robust, that is, they support only exact matching of queries, while we would like to know to what degree the contents in specified structural positions are relevant to those in the query even when the structure does not exactly match the query.