Towards Querying and Mining of Big Graphs KEC 1007 Thursday, February 26, 2015 - 10:00am to 11:00am
Speaker Information Arijit Khan Post-doctorate Researcher Systems Group ETH Zurich Abstract: Given a massive network of interconnected entities such as the Google knowledge graph, how can a user search for an activity at a child-friendly tourist-attraction site inside the New York City that is also close to an Asian restaurant? Freebase that powers Google’s knowledge graph alone has over 22 million entities and 350 million relationships in about 5428 domains. Before users can query anything meaningful over this data, they are often overwhelmed by the daunting task of attempting to even digest and understand it. Without knowing the exact structure of the data and the semantics of the entity labels and their relationships, can we still query them and obtain the relevant results? In this talk, I shall give an overview of our user-friendly and scalable techniques as well as distributed systems for querying of large-scale networks, including knowledge graphs, uncertain and stream graphs. Next, I shall demonstrate a new kind of graph patterns identified by our research th! at are critical in finding the top-k most interesting item sets and the top-k most influential persons in a social network. I will also discuss our newest progress towards indexing for classification queries. Speaker Biography: Arijit Khan is a post-doctorate researcher in the Systems group at ETH Zurich. His research interests span in the area of big-data, big-graphs, and graph systems. He received his PhD from the Department of Computer Science, University of California, Santa Barbara. His PhD dissertation was focused on efficiently answering queries in large-scale social and information networks that are noisy and often lack a fixed schema. Arijit is the recipient of the prestigious IBM PhD Fellowship in 2012-13. He published several papers in premier database and data-mining conferences including SIGMOD, VLDB, ICDE, SDM, and EDBT. Arijit co-presented tutorials on emerging graph queries and big-graph systems at ICDE 2012 and VLDB 2014, and served in the program committee of KDD, ICDM, EDBT, BDMR, and SIGMOD best demo selection committee. Arijit is serving as the co-chair of Big-O(Q) workshop to be co-located with VLDB 2015.
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