Introducing Gravitational Force into Affinity Propagation Clustering
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Xiaofeng Chen,Shitong Wang,Fulai Chung,Suqun Cao. Introducing Gravitational Force into Affinity Propagation Clustering. International Journal of Software and Informatics, 2010,4(2):135~149
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Fund:This work is supported by HongKong PolyU Grant No.G-U296, National 973 Key Project (GrantNo.2006CB705700), 2007 National 863 project (Grant No.2007A- A1Z158), 2007 two grants fromNational Science Foundation of China, 2007 Cultivation Fund of the Key Scientific and TechnicalInnovation Project of Ministry of Education of China, the Key Lab. of Computer InformationTechnologies at JiangSu Province, China.
Abstract:Clustering has long been an important data processing task in different applications. Typically, it attempts to partition the available data into groups according to their underlying distributions, and each cluster is represented by a center or an exemplar. In this paper, a new clustering algorithm called gravitational-force-based affinity propagation (GAP) is proposed, based on the well-known Newton's law of universal gravitation. It views the available data points as nodes of a network (or planets of a universe) and the clusters and their corresponding exemplars can be obtained by transmitting affinity messages based on the gravitational forces between data points in a network. While GAP is inspired by the recently proposed affinity propagation (AP) clustering approach, it provides a new definition of the similarity between data points which makes the AP process more convincing and at the same time facilitates the differentiation of data points' importance. The experimental results show that the GAP clustering algorithm, with comparable clustering accuracy, is even more efficient than the original AP clustering approach.
keywords:clustering  affinity propagation  gravitational force
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