DocumentCode
3276741
Title
The research on topic detection based on multi-models and multi-characteristics
Author
Zhang Su-xiang ; Li Ya-xi ; Wang Xiu-li ; Xie Lin-yan
Author_Institution
State Grid Inf. & Telecommun. Co., Ltd., Beijing, China
fYear
2013
fDate
23-25 May 2013
Firstpage
595
Lastpage
598
Abstract
In this paper, a new approach was proposed for the topic detection, which combined the multi-models and multi-characteristics, entity information similarities were researched as features for support vector machine model (SVM) by us, for example, the content similarity, time similarity and location similarity methods can be proposed respectively, the Bayesian model also can be discussed to obtain the atomic characteristics in this paper. Except this features, the expert knowledge base has been studied to solve the difficult classification problem. The experimental results show that the approach combined the statistical model with expert rule base is effective.
Keywords
Bayes methods; expert systems; information retrieval; support vector machines; text analysis; Bayesian model; SVM; content similarity; entity information similarity; expert knowledge base; expert rule base; location similarity; multicharacteristics; multimodels; statistical model; support vector machine model; time similarity; topic detection; Support vector machine classification; Testing; clustering; entity information similarity; feature selection; support vector model;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
Conference_Location
Beijing
ISSN
2327-0586
Print_ISBN
978-1-4673-4997-0
Type
conf
DOI
10.1109/ICSESS.2013.6615379
Filename
6615379
Link To Document