POLYPHONET: an advanced social network extraction system from the web
Proceedings of the 15th international conference on World Wide Web
Fast Random Walk with Restart and Its Applications
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
ArnetMiner: extraction and mining of academic social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Inferring relevant social networks from interpersonal communication
Proceedings of the 19th international conference on World wide web
Empirical comparison of algorithms for network community detection
Proceedings of the 19th international conference on World wide web
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This paper solves a region-based subgraph discovery problem. We are given a social network and some sample nodes which is supposed to belong to a specific region, and the goal is to obtain a subgraph that contains the sampled nodes with other nodes in the same region. Such regional subgraph discovery can benefit region-based applications, including scholar search, friend suggestion, and viral marketing. To deal with this problem, we assume there is a hidden backbone connecting the query nodes directly or indirectly in their region. The idea is that individuals belonging to the same region tend to share similar interests and cultures. By modeling such fact on edge weights, we search the graph to extract the regional backbone with respect to the query nodes. Then we can expand the backbone to derive the regional network. Experiments on a DBLP co-authorship network show the proposed method can effectively discover the regional subgraph with high precision scores.