文献类型：期刊文献

英文题名：Content-oriented automatic text categorization with the cognitive situation models

作者：Guo, Yi[1]; Shao, Zhiqing[1]; Nan, Hua[2]

机构：[1] Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China; [2] Telecommunication Engineering Institute, Air Force Engineering University, Xi'an, 710077, China

年份：2008

卷号：1

起止页码：512

外文期刊名：Proceedings - International Symposium on Computer Science and Computational Technology, ISCSCT 2008

收录：EI(收录号：20091211972027)

语种：英文

外文关键词：Natural language processing systems - Data mining - Character recognition - Text processing

摘要：Text categorization is an important research field within text mining. The initial objective of text categorization is to recognize, understand and organize various volumes of texts or documents. The general procedures of categorization are treated as supervised learning, from which the similarity can be inferred from a collection of categorized texts for training purpose. Obviously, the typical approaches for categorization are restrained at single word level and not content-oriented. This paper introduces an innovative research work, a content-oriented automatic text categorization algorithm (CogCate), inspired with cognitive situation models, to simulate the human cognitive procedure in the text categorization task. CogCate is not limited with traditional statistics analysis at word level, but includes a process of lexical or semantics analysis, which secures the accuracy of categorization. The evaluation experiments have testified the precision of CogCate. Meanwhile, CogCate tremendously reduces the time and effort spent on training and corpus maintenance, and proves that text categorization can benefit from interdisciplinary research efforts. ? 2008 IEEE.