CGStream: Continuous Correlated Graph Query for Data Streams

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Conference Proceeding
Proc. Of The 21st ACM Conference on Information and Knowledge Management (CIKM-12), 2012, pp. 1183 - 1192
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In this paper, we propose to query correlated graph in a data stream scenario, where given a query graph q an algorithm is required to retrieve all the subgraphs whose Pearsons correlation coe?cients with q are greater than a threshold ? over some graph data ?owing in a stream fashion. Due to the dynamic changing nature of the stream data and the inherent complexity of the graph query process, treating graph streams as static datasets is computationally infeasible or ine?ective. In the paper, we propose a novel algorithm, CGStream, to identify correlated graphs from data stream, by using a sliding window which covers a number of consecutive batches of stream data records
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