Natural Language Information Retrieval by Fuzzy Inference


The KIPS Transactions:PartB , Vol. 8, No. 3, pp. 243-250, Jun. 2001
10.3745/KIPSTB.2001.8.3.243,   PDF Download:

Abstract

The common information retrieval in the e-commerce system is the customer's requests for the merchandise information which is provided by the shopping mall. The rapid increase of online shopping mall and internet users requires more efficient conditional searching method about various goods. Moreover, it is necessary that the set of results should be very relevant to the exact intent of users. To offer relevant information to users, natural language support for information retrieval can be considered. However, the ambiguity of natural language makes difficult to apply to the commercial systems. In this paper, we propose a method for natural language query processing through fuzzy inference for the information retrieval to resolve the ambiguity of natural language. From analysed natural language queries by a morphological analyzer, a template is constructed. Then the template is transformed into a database query using fuzzy inference to offer relevant information to users.


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Cite this article
[IEEE Style]
H. K. Park, J. H. Oh, M. H. Kim, K. S. Choi, K. H. Lee, "Natural Language Information Retrieval by Fuzzy Inference," The KIPS Transactions:PartB , vol. 8, no. 3, pp. 243-250, 2001. DOI: 10.3745/KIPSTB.2001.8.3.243.

[ACM Style]
Hyun K Park, Jong Hoon Oh, Myoung Ho Kim, Key Sun Choi, and Kwang Hyung Lee. 2001. Natural Language Information Retrieval by Fuzzy Inference. The KIPS Transactions:PartB , 8, 3, (2001), 243-250. DOI: 10.3745/KIPSTB.2001.8.3.243.