Top-k star queries on knowledge graphs through semantic-aware bounding match scores
作者：
Highlights：
• We answer star queries on knowledge graphs via semantic-aware bounding match scores.
• We define the match score of an answer based on a knowledge graph embedding model.
• We present a bounding technique to efficiently compute match scores.
• We return the semantically similar answers instead of structurally similar ones.
• We show the effectiveness and efficiency of our method on real-world datasets.
摘要
•We answer star queries on knowledge graphs via semantic-aware bounding match scores.•We define the match score of an answer based on a knowledge graph embedding model.•We present a bounding technique to efficiently compute match scores.•We return the semantically similar answers instead of structurally similar ones.•We show the effectiveness and efficiency of our method on real-world datasets.
论文关键词：Top-k star query,Bounding match score,Semantic similarity
论文评审过程：Received 14 July 2020, Revised 30 October 2020, Accepted 3 December 2020, Available online 18 December 2020, Version of Record 24 December 2020.
论文官网地址：https://doi.org/10.1016/j.knosys.2020.106655
