DMCA
Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis
BibTeX
@MISC{Zhou_integratingvertex-centric,
author = {Yang Zhou and Ling Liu and David Buttler},
title = {Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis},
year = {}
}
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Abstract
Meta paths are good mechanisms to improve the quality of graph analysis on heterogeneous information networks. This paper presents a meta path graph clustering framework, VEPathCluster, that com-bines meta path vertex-centric clustering with meta path edge-centric clustering for improving the clustering quality of heterogeneous networks. First, we propose an edge-centric path graph model to capture the meta-path dependencies between pairwise path edges. We model a heterogeneous network containing M types of meta paths as M vertex-centric path graphs and M edge-centric path graphs. Second, we propose a clustering-based multigraph model to capture the fine-grained clustering-based relationships between pairwise vertices and between pairwise path edges. We perfor-m clustering analysis on both a unified vertex-centric path graph and each edge-centric path graph to generate vertex clustering and edge clusterings of the original heterogeneous network respective-ly. Third, a reinforcement algorithm is provided to tightly integrate vertex-centric clustering and edge-centric clustering by mutually enhancing each other. Finally, an iterative learning strategy is p-resented to dynamically refine both vertex-centric clustering and edge-centric clustering by continuously learning the contributions and adjusting the weights of different path graphs.
Keyphrases
edge-centric clustering meta path graph analysis pairwise path edge heterogeneous network meta path edge-centric path graph vertex-centric clustering pairwise vertex heterogeneous information network vertex clustering unified vertex-centric path graph clustering-based multigraph model different path graph meta path edge-centric clustering reinforcement algorithm iterative learning strategy original heterogeneous network respective-ly meta path graph fine-grained clustering-based relationship vertex-centric path graph good mechanism edge-centric path graph model meta-path dependency graph analysis edge clustering com-bines meta path vertex-centric clustering
