Does Multi-user Document Classification Really Help Knowledge Management?

Abstract

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 context.