Personalized mining of web documents using link structures and fuzzy concept networks

Kyung Joong Kim, Sung Bae Cho

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)


Personalized search engines are important tools for finding web documents for specific users, because they are able to provide the location of information on the WWW as accurately as possible, using efficient methods of data mining and knowledge discovery. The types and features of traditional search engines are various, including support for different functionality and ranking methods. New search engines that use link structures have produced improved search results which can overcome the limitations of conventional text-based search engines. Going a step further, this paper presents a system that provides users with personalized results derived from a search engine that uses link structures. The fuzzy document retrieval system (constructed from a fuzzy concept network based on the user's profile) personalizes the results yielded from link-based search engines with the preferences of the specific user. A preliminary experiment with six subjects indicates that the developed system is capable of searching not only relevant but also personalized web pages, depending on the preferences of the user.

Original languageEnglish
Pages (from-to)398-410
Number of pages13
JournalApplied Soft Computing Journal
Issue number1
Publication statusPublished - 2007 Jan

Bibliographical note

Funding Information:
This research was supported by Brain Science and Engineering Research Program sponsored by Korean Ministry of Commerce, Industry and Energy.

All Science Journal Classification (ASJC) codes

  • Software


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