DocumentCode
2985355
Title
A Topic Partition Algorithm Based on Average Sentence Similarity for Interactive Text
Author
Zhu, Haiping ; Chen, Yan ; Yang, Yang ; Gao, Chao
Author_Institution
Dept. of Comput. Sci. & Technol., Xi´´an Jiaotong Univ., Xi´´an, China
fYear
2011
fDate
3-4 Dec. 2011
Firstpage
427
Lastpage
430
Abstract
Based on the research and analysis of interactive text properties, the word frequency statistics and synonyms merger are imported to obtain the keywords of interactive text. The Sentence similarity is used to describe the degree of coupling between sentences. Then a novel topic partition algorithm based on average sentence similarity is proposed. The experimental results show the effectiveness of the algorithm. Along with the mining of the deep correlations among texts, the algorithm precision and accuracy will be improved.
Keywords
interactive systems; text analysis; average sentence similarity; interactive text properties; synonyms merger; topic partition algorithm; word frequency statistics; Algorithm design and analysis; Computer science; Correlation; Educational institutions; Electronic mail; Partitioning algorithms; Semantics; Average Sentence Similarity component; Frequency Statistics; Interactive Text; Topic Partition;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security (CIS), 2011 Seventh International Conference on
Conference_Location
Hainan
Print_ISBN
978-1-4577-2008-6
Type
conf
DOI
10.1109/CIS.2011.101
Filename
6128060
Link To Document