NDLI: Rough Set Based Approach to Text Classification

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Rough Set Based Approach to Text Classification

Content Provider	ACM Digital Library
Author	Nadee, Wanvimol Zhang, Libiao Sun, Chao Li, Yuefeng
Abstract	Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.
Starting Page	245
Ending Page	252
Page Count	8
File Format	PDF
ISBN	9780769551456
DOI	10.1109/WI-IAT.2013.190
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-11-17
Access Restriction	Subscribed
Subject Keyword	Machine learning text classification feature selection rough set decision making
Content Type	Text
Resource Type	Article

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