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
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;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-4997-0
DOI :
10.1109/ICSESS.2013.6615379