GExp: Cost-aware Graph Exploration with Keywords

We demonstrate GExp, an interactive graph exploration tool that uses keywords to support effective access and exploration of large graphs. GExp interleaves keyword query suggestion, which generates keyword queries that expand the original query, and query evaluation, that returns the answers to suggested queries for feedback. It advocates (1) cost-aware exploration, which suggests keyword queries that have low answer cost (thus high answer quality), and (2) incremental query evaluation to update the query answers with a bounded time cost. It differs from prior systems in its ability to identify and leverage substructures that augment original answers for query expansion and evaluation with provable cost bounds. A unique feature of GExp is that users can trade the quality of query answers with their evaluation cost by tuning the bound of answer cost in an ad-hoc manner. We demonstrate how GExp supports graph exploratory with three established keyword query classes with bounded time cost, and guarantees on result quality, using real-world knowledge bases and information networks.