Text Document Classification and Pattern Recognition

被引：2

作者：

Wu, Qin ^{[1
]}

Fuller, Eddie ^{[1
]}

Zhang, Cun-Quan ^{[1
]}

机构：

[1] W Virginia Univ, Dept Math, Morgantown, WV 26506 USA

来源：

2009 INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING | 2009年

关键词：

D O I：

10.1109/ASONAM.2009.21

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this extended abstract, a novel approach is proposed for text pattern recognition. Instead of the traditional models which are mainly based on the frequency of keywords for text document classification, we introduce a new graph theory model which is constructed based on both information about frequency and position of keywords. We applied this new idea to the detection of fraudulent emails written by the same person, and plagiarized publications. The results on these case studies show that this new method performs much better than traditional methods.

引用

页码：405 / 410

页数：6

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