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Does multi-user document classification really help knowledge management?


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Kang, BH, Kim, YS and Choi, YJ 2007 , 'Does multi-user document classification really help knowledge management?', in MA Orgun and J Thornton (eds.), AI 2007 - Advances in Artificial Intelligence: 20th Australian Joint Conference on Artificial Intelligence, Gold Coast, Australia, December 2-6, 2007, Proceedings , Lecture Notes in Computer Science: Lecture Notes in Artificial Intelligence (4830) , Springer Verlag, Heidelberg, pp. 327-336.

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In general, document classification research focuses on the
automated placement of unseen documents into pre-defined categories. This is
regarded as one core technical component of knowledge management systems,
because it can support to handle explicit knowledge more systematically and
improve knowledge sharing among the users. Document classification in
knowledge management systems should support incremental knowledge
acquisition and maintenance because of the dynamic knowledge changes
involved. We propose the MCRDR document classifier as an incremental and
maintainable document classification solution. Even though our system
successfully supported personal level document classification, we did not
examine its capability as a document classification tool in multi-user based
knowledge management contexts. This paper focuses on the analysis of
document classification results performed by multiple users. Our analysis
reveals that even though the same documents and the classification structure are
given to the users, they have very different document classification patterns and
different acceptance results for each other’s classification results. Furthermore,
our results show that the integration of multiple users’ classification may
improve document classification performance in the knowledge management

Item Type: Book Section
Authors/Creators:Kang, BH and Kim, YS and Choi, YJ
Keywords: Knowledge Management, Document Classification, MCRDR.
Publisher: Springer Verlag
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