DocumentCode :
2163307
Title :
Elimination of redundant information for search engine
Author :
Ming, Zhu ; Xi, Guo ; Yan, CaiRong ; SuHouQin
Author_Institution :
College of Computer Science and Technology, Donghua University, Shanghai, China
fYear :
2010
fDate :
4-6 Dec. 2010
Firstpage :
2038
Lastpage :
2041
Abstract :
The results of search engine usually contain a number of redundant information and how to eliminate it has become technology issues waiting to be explored. This paper proposed an improved elimination algorithm based on best similarity of the results. By analyzing the search results, extracting their key words, comparing the similarities, and clustering the results, the algorithm can eliminate the useless and reduplicate results. The experimental results show that the performance of the elimination algorithm in this paper has been much improved compared to spectral segmentation algorithm.
Keywords :
Classification algorithms; Clustering algorithms; Communities; Computer science; Educational institutions; Google; Search engines; Search engine; clustering; redundant information; similarity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
Type :
conf
DOI :
10.1109/ICISE.2010.5691839
Filename :
5691839
Link To Document :
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