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We witness an unprecedented proliferation of knowledge graphs that recordmillions of entities and their relationships. While knowledge graphs arestructure-flexible and content rich, they are difficult to use. The challengelies in the gap between their overwhelming complexity and the limited databaseknowledge of non-professional users. If writing structured queries over simpletables is difficult, complex graphs are only harder to query. As an initialstep toward improving the usability of knowledge graphs, we propose to querysuch data by example entity tuples, without requiring users to form complexgraph queries. Our system, GQBE (Graph Query By Example), automatically derivesa weighted hidden maximal query graph based on input query tuples, to capture auser's query intent. It efficiently finds and ranks the top approximate answertuples. For fast query processing, GQBE only partially evaluates query graphs.We conducted experiments and user studies on the large Freebase and DBpediadatasets and observed appealing accuracy and efficiency. Our system provides acomplementary approach to the existing keyword-based methods, facilitatinguser-friendly graph querying. To the best of our knowledge, there was no suchproposal in the past in the context of graphs.

Querying Knowledge Graphs by Example Entity Tuples