DocumentCode
3048418
Title
Study on key technology of topic tracking based on VSM
Author
Li, Shengdong ; Lv, Xueqiang ; Zhou, Qiang ; Shi, Shuicai
Author_Institution
Chinese Inf. Process. Res. Center, Beijing Inf. Sci. & Technol. Univ., Beijing, China
fYear
2010
fDate
20-23 June 2010
Firstpage
2419
Lastpage
2423
Abstract
Text classification is the key technology for topic tracking, and vector space model (VSM) is one of the most simple and effective models for topics representation. On the basis of 2 information gain algorithm and chi square ιY in VSM, we have studied how feature selection algorithm and feature dimension in VSM affect topic tracking. And then we get the variation law that they affect topic tracking, and add up their optimal values in topic tracking. Finally, TDT evaluation method proves that their optimal values can make topic tracking gain very good tracking performance. In addition, we also prove in 2 the experiment that chi square ιY in VSM has better performance for topic tracking than information gain algorithm.
Keywords
learning (artificial intelligence); pattern classification; text analysis; VSM; feature dimension; feature selection algorithm; information gain algorithm; key technology study; text classification; topic representation model; topic tracking; vector space model; Automation; Classification algorithms; Information processing; Information science; Multimedia databases; Performance gain; Prototypes; Space technology; Testing; Text categorization; KNN; TDT Evaluation; Topic Tracking; VSM;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Automation (ICIA), 2010 IEEE International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4244-5701-4
Type
conf
DOI
10.1109/ICINFA.2010.5512284
Filename
5512284
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