The explosion of user-generated data from online social networks stimulates the analysis that extracts deep insights from the data. As the data items exhibit rich connections (e.g., they can be connected by social relation, time, location, and topics), it is natural to study them in the form of a graph. Moreover, such a graph evolves over time, trending topics and social activities are constantly changing. We are building systems to enable the storage and analysis on a time evolving graph.
- Vijayan Prabhakaran, Ming Wu, Xuetian Weng, Frank McSherry, Lidong Zhou, and Maya Haridasan, Managing Large Graphs on Multi-Cores with Graph Awareness , in USENIX Annual Technical Conference (USENIX ATC'12), USENIX, June 2012
- Raymond Cheng, Ji Hong, Aapo Kyrola, Youshan Miao, Xuetian Weng, Ming Wu, Fan Yang, Lidong Zhou, Feng Zhao, and Enhong Chen, Kineograph: taking the pulse of a fast-changing and connected world, ACM Eurosys, April 2012