DocumentCode :
3429269
Title :
Identifying Topics by using Word Distribution
Author :
Nakayama, Motoi ; Miura, Takao
Author_Institution :
Hosei Univ., Tokyo
fYear :
2007
fDate :
22-24 Aug. 2007
Firstpage :
245
Lastpage :
248
Abstract :
In this work, we examine and verify a topic word model which says each topic can be identified by means of word distribution under same author, and by using random projection, one of the dimension reduction techniques, we show we can obtain efficient and effective processing to the model. We examine Shakespeare works and show we can identify scenes correctly to their dramas.
Keywords :
word processing; authorship problem; dimension reduction techniques; random projection; topic word a model; word distribution; Broadcasting; Data mining; Frequency; Information retrieval; Layout; Machine learning; Probability distribution; Stress; Tail;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computers and Signal Processing, 2007. PacRim 2007. IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4244-1189-4
Electronic_ISBN :
1-4244-1190-4
Type :
conf
DOI :
10.1109/PACRIM.2007.4313221
Filename :
4313221
Link To Document :
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