Yixiang Fang

Effective community search over large spatial graphs

Communities are prevalent in social networks, knowledge graphs, and biological networks. Recently, the topic of community search (CS) has received plenty of attention. Given a query vertex, CS looks for a dense subgraph that contains it. Existing CS solutions do not consider the spatial extent of a community. They can yield communities whose locations of vertices span large areas. In applications that facilitate the creation of social events (e.g., finding conference attendees to join a dinner), it is important to find groups of people who are physically close to each other. In this situation, it is desirable to have a spatial-aware community (or SAC), whose vertices are close structurally and spatially. Given a graph G and a query vertex q, we develop exact solutions for finding an SAC that contains q. Since these solutions cannot scale to large datasets, we have further designed three approximation algorithms to compute an SAC. We have performed an experimental evaluation for these solutions on both large real and synthetic datasets. Experimental results show that SAC is better than the communities returned by existing solutions. Moreover, our approximation solutions can find SACs accurately and efficiently.

Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data

Trajectory data are prevalent in systems that monitor the locations of moving objects. In a location-based service, for instance, the positions of vehicles are continuously monitored through GPS; the trajectory of each vehicle describes its movement history. We study joins on two sets of trajectories, generated by two sets

Walking in the cloud: parallel SimRank at scale

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Querying Minimal Steiner Maximum-Connected Subgraphs in Large Graphs

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C-explorer: browsing communities in large graphs

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On Embedding Uncertain Graphs

of moving objects. For each entity in

Scalable algorithms for nearest-neighbor joins on big trajectory data

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STEM: a suffix tree-based method for web data records extraction

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Effective and efficient attributed community search

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On Attributed Community Search

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