International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Since Year 2012 | Open Access | Double Blind Reviewed

ISSN: 2319-7064


Downloads: 127

M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 4 Issue 12, December 2015


Streaming Data Clustering by Incremental Affinity Propagation

Jismy Muhammed


Abstract: This paper introdused based on clustering. Affinity Propagation (AP) clustering has been successfully used in a lot of clustering problems. This paper considers how to apply AP in incremental clustering problems in streams of data. First, we point out the difficulties in Incremental Affinity Propagation (IAP) clustering, and then propose two strategies to solve them. Two IAP clustering algorithms are proposed. They are IAP clustering based on K-Medoids (IAPKM) and IAP clustering based on Nearest Neighbor Assignment (IAPNA). Traditional AP clustering is also implemented to provide benchmark performance. Experimental results show that IAPKM and IAPNA can achieve comparable clustering performance with traditional AP clustering on all the data sets. Popular labeled data sets, real world time series and a video, datastreams are used to test the performance of IAPKM and IAPNA. Both the effectiveness and the efficiency make IAPKM and IAPNA able to be well used in incremental clustering tasks.


Keywords: Affinity propagation, incremental clustering, K-medoids, nearest neighbor assignment


Edition: Volume 4 Issue 12, December 2015,


Pages: 108 - 111


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How to Cite this Article?

Jismy Muhammed, "Streaming Data Clustering by Incremental Affinity Propagation", International Journal of Science and Research (IJSR), Volume 4 Issue 12, December 2015, pp. 108-111, https://www.ijsr.net/get_abstract.php?paper_id=NOV151831

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