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Research Papers

A Customizable Text Classifier for Text Mining

Authors
  • Yun-liang Zhang
  • Quan Zhang

Abstract

Text mining deals with complex and unstructured texts. Usually a particular collection of texts that is specified to one or more domains is necessary. We have developed a customizable text classifier for users to mine the collection automatically. It derives from the sentence category of the HNC theory and corresponding techniques. It can start with a few texts, and it can adjust automatically or be adjusted by user. The user can also control the number of domains chosen and decide the standard with which to choose the texts based on demand and abundance of materials. The performance of the classifier varies with the user's choice.
Year: 2007
Volume 6
Page/Article: S904-S909
DOI: 10.2481/dsj.6.S904
Published on Dec 19, 2007
Peer Reviewed