Department of Computer Science
GBLENDER: Visual subgraph query formulation meets query processing
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 demonstrate a system called GBLENDER that exploits GUI latency to prune false results and prefetch candidate data graphs by employing a novel action-aware indexing scheme and a data structure called spindle-shaped graphs (SPIG). We demonstrate various innovative features of GBLENDER and its promising performance in evaluating subgraph containment and similarity queries. © 2011 Authors.
frequent subgraphs, graph databases, graph indexing, infrequent subgraphs, prefetching, visual query formulation
Source Publication Title
SIGMOD '11 Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Link to Publisher's Edition
Jin, C., Bhowmick, S., Xiao, X., Choi, B., & Zhou, S. (2011). GBLENDER: Visual subgraph query formulation meets query processing. SIGMOD '11 Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, 1327-1330. https://doi.org/10.1145/1989323.1989489