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- W2897555839 abstract "Community discovery in a dynamic heterogeneous information network is a challenging topic and quite more difficult than that in a traditional static homogeneous information network. Community in heterogeneous information network, named multi-typed community, contains multiple types of dynamic objects and links, which brings three challenges. Firstly, the multi-typed communities are heterogeneous. Secondly, The communities are constantly changing along time. Finally, the network schemas for different heterogeneous information networks are various. To overcome these challenges, we propose a multi-typed community discovery method for dynamic heterogeneous information networks through tensor method without the restriction of network schema. A tensor decomposition framework is designed to model the multi-typed community and address the community evolution. Experimental result on a real-world dataset demonstrates the efficiency of our framework." @default.
- W2897555839 created "2018-10-26" @default.
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- W2897555839 date "2017-12-01" @default.
- W2897555839 modified "2023-09-25" @default.
- W2897555839 title "Multi-typed Community Discovery in Dynamic Heterogeneous Information Networks through Tensor Method" @default.
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- W2897555839 doi "https://doi.org/10.1109/apwconcse.2017.00019" @default.
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