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
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;
Conference_Titel :
Computational Intelligence and Security (CIS), 2011 Seventh International Conference on
Conference_Location :
Hainan
Print_ISBN :
978-1-4577-2008-6
DOI :
10.1109/CIS.2011.101
