杨秀隆-2016.3.14-多层网络聚落检测综述

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标题：杨秀隆-2016.3.14-多层网络聚落检测综述
报告人：杨秀隆

摘要：本文介绍多层网络下聚落检测问题， 并对相应算法做综述。 涉及主要算法分类：

1. 聚类扩展 cluster expansion
2. 矩阵分解 matrix factorization
3. 统一距离？ unified distance
4. 基于概率模型 model based
5. 模式挖掘 pattern mining
6. 图合并 graph merging

涉及论文：

1. 聚类扩展 Scalable community discovery on textual data with relations 文章链接
2. 统一距离  Graph clustering based on structural/attribute similarities    文章链接
3. 基于概率模型  Z. Xu, Y. Ke, Y. Wang, H. Cheng, and J. Cheng. A model-based approach to attributed graph clustering  文章链接
4. 图合并 Y. Ruan, D. Fuhry, and S. Parthasarathy. Efficient community detection in large networks using content and links   文章链接
5. 矩阵分解 Community Detection with Edge Content in Social Media Networks 文章链接
6. 模式挖掘 Coherent Closed Quasi-Clique Discovery from Large Dense Graph Databases 文章链接
      和  Mining Coherent Subgraphs in Multi-Layer Graphs with Edge Labels  文章链接

报告PPT 见 多层网络聚落检测综述