Search Result Clustering Using Fuzzy C-Mean and Gustafon Kessel Algorithms: A Comparative Study


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.


    5 Figures and Tables

    Download Full PDF Version (Non-Commercial Use)