A New Method Based on Fuzzy C-Means Algorithm for Search Results Clustering

  • Fei Wang
  • Yueming Lu
  • Fangwei Zhang
  • Songlin Sun
Part of the Communications in Computer and Information Science book series (CCIS, volume 320)


The existing Fuzzy C-means (FCM) clustering algorithm can only cluster the web documents samples with a pre-known cluster number c which is impossible in practical situations. A new method based on fuzzy c-means algorithm for search results clustering is proposed in this paper. The new clustering method combines FCM algorithm with Affinity Propagation (AP) algotithm to find the optimal c for search results. It is proved that the new method has a better performance in accuracy than traditional method in search results clustering.


clustering algorithm search engine results clustering FCM similarity measure 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Fei Wang
    • 1
    • 2
  • Yueming Lu
    • 1
    • 2
  • Fangwei Zhang
    • 3
  • Songlin Sun
    • 1
    • 2
  1. 1.School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Key Laboratory of Trustworthy Distributed Computing and Service (BUPT)Ministry of EducationBeijingChina
  3. 3.School of HumanitiesBeijing University of Posts and TelecommunicationsBeijingChina

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