DocumentCode
3261958
Title
A fast chinese web-document clustering method under Pareto’s Principle
Author
Tianlei, Zhang ; Guishen, Chen ; Hao, Che
Author_Institution
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing
fYear
2008
fDate
26-28 Aug. 2008
Firstpage
801
Lastpage
804
Abstract
Nowadays most search engine like Google, Baidu, demonstrate their query results by the value of item, listing them in several pages. As we are now in an age of information explosion, the number of pages will be huge and users have to glance over several before they get what they want. If we cluster the results, this problem will be solved. There are several clustering methods, but not quite accurate and efficient, especially when the result sets are consist of millions of items. this article describe an fast method under Paretopsilas Principle.
Keywords
document handling; pattern clustering; search engines; Baidu; Chinese Web-document clustering method; Google; Pareto principle; information explosion; search engine; Artificial intelligence; Clustering algorithms; Clustering methods; Explosions; Internet; Machine learning algorithms; Search engines; Systems engineering and theory; Testing; Web pages;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2008. GrC 2008. IEEE International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-2512-9
Electronic_ISBN
978-1-4244-2513-6
Type
conf
DOI
10.1109/GRC.2008.4664707
Filename
4664707
Link To Document