A customizable text classifier for text mining

被引：0

作者：

Zhang, Yun-Liang ^{[1
]}

Zhang, Quan ^{[2
]}

机构：

[1] Institute of Acoustics, Graduate School, Chinese Academy of Sciences

[2] Institute of Acoustics, Chinese Academy of Sciences

来源：

Data Science Journal | 2007年 / 6卷 / SUPPL.期

关键词：

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

D O I：

10.2481/dsj.6.S904

中图分类号：

学科分类号：

摘要：

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.

引用

页码：S904 / S909

页数：5

共 20 条

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