User feedback-driven document clustering technique for information organization

Han Joon Kim, Sang Goo Lee

Research output: Contribution to journalLetterpeer-review

3 Scopus citations


This paper discusses a new type of semi-supervised document clustering that uses partial supervision to partition a large set of documents. Most clustering methods organizes documents into groups based only on similarity measures. In this paper, we attempt to isolate more semantically coherent clusters by employing the domain-specific knowledge provided by a document analyst. By using external human knowledge to guide the clustering mechanism with some flexibility when creating the clusters, clustering efficiency can be considerably enhanced. Experimental results show that the use of only a little external knowledge can considerably enhance the quality of clustering results that satisfy users' constraint.

Original languageEnglish
Pages (from-to)1043-1048
Number of pages6
JournalIEICE Transactions on Information and Systems
Issue number6
StatePublished - Jun 2002


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