DocumentCode :
2261261
Title :
LDA Based Related Word Detection in Advertising
Author :
Jin, Xin ; Xia, Huan ; Li, Juanzi
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
fYear :
2010
fDate :
20-22 Aug. 2010
Firstpage :
90
Lastpage :
94
Abstract :
In this paper, we propose a new method for related word detection in Advertising by combining LDA topic model and word co-occurrence. We use a corpus of BaiduBaike, which is a Chinese Encyclopedia, to calculate the word co-occurrence. Words allocation on topics driven by LDA is used to sort the related words glossary which is obtained by the traditional co-occurrence procedure. We evaluate our method on advertising related word recognition, and the experiments result shows that the method is feasible.
Keywords :
advertising; character recognition; encyclopaedias; word processing; BaiduBaike corpus; Chinese encyclopedia; LDA based related word detection; advertising; word allocation; word cooccurrence; word recognition; Advertising; Context; Entropy; Noise; Probability distribution; Semantics; Terminology; Advertising; Context; Entropy; LDA; Related Words; Similarity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Information Systems and Applications Conference (WISA), 2010 7th
Conference_Location :
Hohhot
Print_ISBN :
978-1-4244-8440-9
Type :
conf
DOI :
10.1109/WISA.2010.35
Filename :
5581392
Link To Document :
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