Querying knowledge Graphs By Example entity tuples
Querying knowledge Graphs By Example entity tuples
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DOI：
10.1109/icde.2016.7498391
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Nandish Jayaram;Arijit Khan;Chengkai Li;Xifeng Yan;R. Elmasri
中科院分区：
文献类型：
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作者：
Nandish Jayaram;Arijit Khan;Chengkai Li;Xifeng Yan;R. Elmasri
我们见证了前所未有的知识图谱的激增，这些图谱记录了数百万个实体及其关系。虽然知识图谱结构灵活且内容丰富，但它们很难使用。其挑战在于其压倒性的复杂性与非专业用户有限的数据库知识之间的差距。作为提高知识图可用性的第一步，我们建议通过示例实体元组来查询此类数据，而不需要用户形成复杂的图查询。我们的系统，GQBE（图形查询的例子），自动发现一个加权隐藏的最大查询图的基础上输入的查询元组，捕捉用户的查询意图。然后，它有效地找到排名靠前的近似答案图和答案元组。
We witness an unprecedented proliferation of knowledge graphs that record millions of entities and their relationships. While knowledge graphs are structure-flexible and content-rich, they are difficult to use. The challenge lies in the gap between their overwhelming complexity and the limited database knowledge of non-professional users. As an initial step toward improving the usability of knowledge graphs, we propose to query such data by example entity tuples, without requiring users to form complex graph queries. Our system, GQBE (Graph Query By Example), automatically discovers a weighted hidden maximum query graph based on input query tuples, to capture a user's query intent. It then efficiently finds top-ranked approximate answer graphs and answer tuples.