The bootstrapping based recognition of conceptual relationship for text retrieval

Authors:
Yi Hu;Ruzhan Lu;Yuquan Chen;Xiaoying Chen;Jianyong Duan
Affiliations:
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Venue:
NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
Year:
2007

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Abstract

The dependence analysis is usually the key for improving the performance of text retrieval. Compared with the statistical value of a conceptual relationship, the recognition of relation type between concepts is more meaningful. In this paper, we explored a bootstrapping method for automatically extracting semantic patterns from a large-scale corpus to identify the geographical "be part of" relationship between Chinese location concepts in contexts. Our contributions different from other bootstrapping methods lie in: (1) introducing a bi-sequence alignment algorithm in bio-informatics to generating candidate patterns, and (2) giving a new evaluating metric for patterns' confidence to enhance their extracting qualities in next iteration. In terms of automatic recognition of "be part of" relationship, the experiments showed that the pattern set generated by our method achieves higher coverage and precision than DIPRE does.