FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.

It is important to cluster heterogeneous information networks. A fast clustering algorithm based on an approximate commute time embedding for heterogeneous information networks with a star network schema is proposed in this paper by utilizing the sparsity of heterogeneous information networks. First...

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Main Authors: Jing Yang, Limin Chen, Jianpei Zhang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4474961?pdf=render
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spelling doaj-46106fae169e4009bf2f5128ea8f10c22020-11-24T21:24:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01106e013008610.1371/journal.pone.0130086FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.Jing YangLimin ChenJianpei ZhangIt is important to cluster heterogeneous information networks. A fast clustering algorithm based on an approximate commute time embedding for heterogeneous information networks with a star network schema is proposed in this paper by utilizing the sparsity of heterogeneous information networks. First, a heterogeneous information network is transformed into multiple compatible bipartite graphs from the compatible point of view. Second, the approximate commute time embedding of each bipartite graph is computed using random mapping and a linear time solver. All of the indicator subsets in each embedding simultaneously determine the target dataset. Finally, a general model is formulated by these indicator subsets, and a fast algorithm is derived by simultaneously clustering all of the indicator subsets using the sum of the weighted distances for all indicators for an identical target object. The proposed fast algorithm, FctClus, is shown to be efficient and generalizable and exhibits high clustering accuracy and fast computation speed based on a theoretic analysis and experimental verification.http://europepmc.org/articles/PMC4474961?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Jing Yang
Limin Chen
Jianpei Zhang
spellingShingle Jing Yang
Limin Chen
Jianpei Zhang
FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.
PLoS ONE
author_facet Jing Yang
Limin Chen
Jianpei Zhang
author_sort Jing Yang
title FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.
title_short FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.
title_full FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.
title_fullStr FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.
title_full_unstemmed FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.
title_sort fctclus: a fast clustering algorithm for heterogeneous information networks.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description It is important to cluster heterogeneous information networks. A fast clustering algorithm based on an approximate commute time embedding for heterogeneous information networks with a star network schema is proposed in this paper by utilizing the sparsity of heterogeneous information networks. First, a heterogeneous information network is transformed into multiple compatible bipartite graphs from the compatible point of view. Second, the approximate commute time embedding of each bipartite graph is computed using random mapping and a linear time solver. All of the indicator subsets in each embedding simultaneously determine the target dataset. Finally, a general model is formulated by these indicator subsets, and a fast algorithm is derived by simultaneously clustering all of the indicator subsets using the sum of the weighted distances for all indicators for an identical target object. The proposed fast algorithm, FctClus, is shown to be efficient and generalizable and exhibits high clustering accuracy and fast computation speed based on a theoretic analysis and experimental verification.
url http://europepmc.org/articles/PMC4474961?pdf=render
work_keys_str_mv AT jingyang fctclusafastclusteringalgorithmforheterogeneousinformationnetworks
AT liminchen fctclusafastclusteringalgorithmforheterogeneousinformationnetworks
AT jianpeizhang fctclusafastclusteringalgorithmforheterogeneousinformationnetworks
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