Hyo Lae Kim, Young Cheol Jang, Chang Hoon Lee

The KIPS Transactions:PartB , Vol. 8, No. 6, pp. 657-668, Dec. 2001
10.3745/KIPSTB.2001.8.6.657,   PDF Download:

Abstract

It is difficult that web documents are classified with exact user intention because existing document classification systems are based on word frequency number using single keyword. To improve this defect, first, we use keyword, a query, domain knowledge. Like explanation based learning, first, query is analyzed with knowledge based information and then structured user intention information is extracted. We use this intention tree in the course of existing word frequency number based document classification as user information and constraints. Thus, we can classify web documents with more exact user intention. In classifying document, structured user intention information is helpful to keep more documents and information which can be lost in the system using single keyword information. Our hybrid approach integrating user intention information with existing statistics and probability method is more efficient to decide direction and range of document category than existing word frequency approach.

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