Natural Language Information Retrieval by Fuzzy Inference


KIPS Transactions on Computer and Communication Systems, 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.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
H. K. Park, J. H. Oh, M. H. Kim, K. S. Choi and K. H. Lee, "Natural Language Information Retrieval by Fuzzy Inference," KIPS Journal B (2001 ~ 2012) , 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. KIPS Journal B (2001 ~ 2012) , 8, 3, (2001), 243-250. DOI: 10.3745/KIPSTB.2001.8.3.243.