Title :
Search Result Clustering Using Fuzzy C-Mean and Gustafon Kessel Algorithms: A Comparative Study
Author :
Al-Dubaee, Shawki A. ; Ahmad, Nesar
Author_Institution :
Dept. of Comput. Eng., Aligarh Muslim Univ., Aligarh, India
Abstract :
During the last few years, the search result clustering has attracted a substantial amount of research. In this paper, we present a comparative study of the performance of fuzzy clustering algorithms, namely Fuzzy C-Means (FCM), and Gustafson-Kessel (GK) algorithms with clustering search results. Therefore, there is a need to reduce the information, help filtering out irrelevant items, and favors exploration of unknown or dynamic domains in a better way by clustering the search results.
Keywords :
Internet; fuzzy set theory; information filtering; pattern clustering; search engines; Gustafon Kessel algorithm; fuzzy C-mean algorithm; fuzzy clustering; irrelevant item filtering; search engine; search result clustering; Algorithm design and analysis; Clustering algorithms; Heuristic algorithms; Indexes; Internet; Partitioning algorithms; Search engines; Fuzzy C-Mean; Gustafon kessel; cluster analysis; search engine;
Conference_Titel :
Integrated Intelligent Computing (ICIIC), 2010 First International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-7963-4
Electronic_ISBN :
978-0-7695-4152-5
DOI :
10.1109/ICIIC.2010.50
