Title :
Sequence Alignment Algorithm in Similarity Measurement
Author :
Le, Li ; Hongchang, Chen ; Lixiong, Liu
Author_Institution :
Nat. Digital Switching Syst. Eng. & Technol. R&D Center, Zhengzhou, China
Abstract :
The first and foremost question needed to be considered in clustering analysis is how to measure the similarity that decides the result of clustering immediately. However, are many shortcomings in traditional methods. This paper deals with similarity of English texts using sequence alignment which is always used in biology informatics. This method do not use traditional way that transform texts so that it is more intuitive. It can improve the rate and the result of clustering preferably. The test demonstrates the new approach is reasonable and efficient.
Keywords :
pattern clustering; text analysis; English texts; biology informatics; clustering analysis; sequence alignment; similarity measurement; Algorithm design and analysis; Clustering algorithms; Covariance matrix; Information analysis; Information technology; Partitioning algorithms; Research and development; Sequences; Switching systems; Systems engineering and theory; clustering; sequence alignment; similarity;
Conference_Titel :
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3600-2
DOI :
10.1109/IFITA.2009.119