[1]WU Fei,FENG Hua-min,SHEN Xiao-ye.Research on event detection based on the tolerance rough set model[J].CAAI Transactions on Intelligent Systems,2009,4(2):112-117.
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Research on event detection based on the tolerance rough set model

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 4 Number of periods: 2009 2 Page number: 112-117 Column: 学术论文—人工智能基础 Public date: 2009-04-25
Title:
Research on event detection based on the tolerance rough set model
Author(s):
WU Fei1;  FENG Hua-min1; 2;  SHEN Xiao-ye1
1. School of Telecommunication Engineering, Xidian University, Xi’an 710071，China;
2. Multimedia Intelligent Information Processing Laberatory,Beijing Electronic Science and Technology Institution, Beijing 100070, China
Keywords:
event detection;  rough set;  tolerance rough set model
CLC:
TP391
DOI:
-
Abstract:
Proper monitoring of the content of web news is crucial to the maintenance of network content security. Current text representational models are not suitable for web news because of the sparseness of text representation and the drifting of key words in event tracking processes. To solve these problems, a modeling method for text representation based on tolerance rough sets was used to extend text representation. Following theoretical analysis and experimental verification, we constructed a tolerance rough set for feature terms by considering the vector space model (VSM) and the cooccurrences of feature terms in test sets. Then the tolerance rough set model of tests was generated using the tolerance rough set for feature terms, which extended the original text representation model. Finally, the similarities of texts were described by the feature term’s tolerance classes. Experimental results showed that the tolerance rough set model improved the performance of event detection systems.
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