BibTeX
@MISC{Kashyap_asurvey,
author = {Preeti Kashyap and Babita Ujjainiya},
title = {A Survey On Seeds Affinity Propagation},
year = {}
}
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Abstract
Affinity propagation (AP) is a clustering method that can find data centers or clusters by sending messages between pairs of data points. Seed Affinity Propagation is a novel semisupervised text clustering algorithm which is based on AP. AP algorithm couldn’t cope up with part known data direct. Therefore, focusing on this issue a semi-supervised scheme called incremental affinity propagation clustering is present in the paper where pre-known information is represented by adjusting similarity matrix The standard affinity propagation clustering algorithm also suffers from a limitation that it is hard to know the value of the parameter “preference ” which can yield an optimal clustering solution. This limitation can be overcome by a method named, adaptive affinity propagation. The method first finds out the range of “preference”, then searches the space of “preference ” to find a good value which can optimize the clustering result. Keywords- Affinity propagation, Clustering, Incremental, Partition adaptive affinity propagation
Keyphrases
seed affinity propagation affinity propagation data point data center incremental affinity propagation clustering ap algorithm couldn standard affinity propagation clustering result adaptive affinity propagation keywords affinity propagation pre-known information good value semi-supervised scheme parameter preference optimal clustering solution
