Affinity propagation clustering using path based similarity
type: Item
instance of: scholarly article
title: Affinity propagation clustering using path based similarity
zbMATH Open document ID: 1461.62099
author: Yuan Jiang
author: Yuliang Liao
author: Guoxian Yu
published in: Algorithms
publication date: 2019-03-26T00:00:00Z
review text: Summary: Clustering is a fundamental task in data mining. Affinity propagation clustering (APC) is an effective and efficient clustering technique that has been applied in various domains. APC iteratively propagates information between affinity samples, updates the responsibility matrix and availability matrix, and employs these matrices to choose cluster centers (or exemplars) of respective clusters. However, since it mainly uses negative Euclidean distance between exemplars and samples as the similarity between them, it is difficult to identify clusters with complex structure. Therefore, the performance of APC deteriorates on samples distributed with complex structure. To mitigate this problem, we propose an improved APC based on a path-based similarity (APC-PS). APC-PS firstly utilizes negative Euclidean distance to find exemplars of clusters. Then, it employs the path-based similarity to measure the similarity between exemplars and samples, and to explore the underlying structure of clusters. Next, it assigns non-exemplar samples to their respective clusters via that similarity. Our empirical study on synthetic and UCI datasets shows that the proposed APC-PS significantly outperforms original APC and other related approaches.
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62H35
Mathematics Subject Classification ID: 94A08
Mathematics Subject Classification ID: 94C15
zbMATH DE Number: 7042355
zbMATH Keywords: clustering
zbMATH Keywords: affinity propagation
zbMATH Keywords: path-based similarity
zbMATH Keywords: complex structure
describes a project that uses: UCI-ml
describes a project that uses: APCluster
describes a project that uses: Algorithm 97
describes a project that uses: apcluster
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/a9030046
OpenAlex ID: W2478474715
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cites work: On clustering validation techniques
DOI: 10.3390/A9030046
description: scientific article; zbMATH DE number 7042355