A dynamic variant of AP clustering to achieve comparable clustering performance
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2015, Vol 4, Issue 11
Abstract
AP clustering is a model based system that fathoms by handover every information point to its closest model, where models are recognized by passing messages on bipartite chart. There are two sorts of messages going on bipartite diagram. They are obligation and accessibility, all in all called 'affinity'. The objective of this paper is to recommendation a dynamic variation of AP grouping, which can achieve proportionate bunching execution with customary AP grouping by simply tinker with the present grouping results as per new arriving objects, somewhat than reactualized AP clustering overall dataset. Along these lines, a lot of time can be spared, which makes AP clustering all around composed adequate to be utilized as a part of element environment.
Authors and Affiliations
K Sujitha, K Ravi Kumar
Keywords
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