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CQIG: An Improved Web Search Results Clustering Algorithm

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2 Author(s)
Yong-gong Ren ; Sch. of Comput. & Inf. Technol., Liaoning Normal Univ., Dalian, China ; Fan Dan

Massive linear search results returned from traditional search engines bring much inconvenience to users when extract the information they need. Search result clustering is of critical need for grouping similar topics of documents. The existing algorithm has drawbacks in clustering labels screening, cluster quality assessment, overlapping clusters controlling. The improved clustering algorithm-CQIG, which based on LINGO, improved the cluster and cluster label scoring function, increased the cluster merging process and improved the processing effect of Chinese. Finally, a recommended platform for Web search results clustering is established based on carrot framework to prove the accuracy, distinction and readability of CQIG.

Published in:

Web Information Systems and Applications Conference (WISA), 2010 7th

Date of Conference:

20-22 Aug. 2010