DocumentCode
690251
Title
An improved method of statistical model for text segmentation
Author
Xiaojin Li ; Aili Han
Author_Institution
Dept. of Comput. Sci., Shandong Univ., Weihai, China
fYear
2013
fDate
15-17 Nov. 2013
Firstpage
282
Lastpage
285
Abstract
Every document contains multiple topics, and the task of text segmentation is to segment a text into several parts that each part represents one topic. On the base of statistical model of Masao Utiyama whose experiment showed that the method was more accurate than or at least as accurate as a state-of-art text segmentation system, this paper proposes an improvement suggestion trying to improve the existing problem. The experiment results showed that the improved algorithm improved both the efficiency and the accuracy.
Keywords
statistical analysis; text analysis; Masao Utiyama; statistical model; text segmentation system; Accuracy; Semantics; artificial intelligence; dynamic programming; text segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronics Information and Emergency Communication (ICEIEC), 2013 IEEE 4th International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/ICEIEC.2013.6835506
Filename
6835506
Link To Document