VOGUE: Towards A Visual Interaction-aware Graph Query Processing Framework

Due to the complexity of graph query languages, the need for visual query interfaces that can reduce the burden of query formulation is fundamental to the spreading of graph data management tools to wider community. We present a novel hci (human-computer interaction)-aware graph query processing paradigm, where instead of processing a query graph after its construction, it interleaves visual query construction and processing to improve system response time. We present the architecture of a system called vogue that exploits gui latency to prune false results and prefetch candidate data graphs by employing a novel action-aware indexing and query processing schemes. We discuss various non-traditional design challenges and innovative features of vogue and highlight its practicality in evaluating subgraph queries.

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