A Customizable Text Classifier for Text Mining

Yun-liang Zhang; Quan Zhang

doi:10.2481/dsj.6.S904

A Customizable Text Classifier for Text Mining

Authors

Yun-liang Zhang Institute of Acoustics, Graduate School, Chinese Academy of Sciences, Beijing 100080, China
Quan Zhang Institute of Acoustics of the Chinese Academy of Sciences, Beijing 100080, China

DOI:

https://doi.org/10.2481/dsj.6.S904

Keywords:

Text mining, Text categorization, Nature Language Processing (NPL)

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.

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Published

2007-12-19

Issue

Vol. 6 (2007)

Section

Research Papers

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