Semantic Guided and Response Times Bounded Top-k Similarity Search over Knowledge Graphs
Semantic Guided and Response Times Bounded Top-k Similarity Search over Knowledge Graphs A summary of the IEEE ICDE 2020 research paper by Yuxiang Wang, Arijit Khan, Tianxing Wu, Jiahui Jin, and Haijiang Yan. Background: Knowledge graphs (such as DBpedia [1], Yago [2], and Freebase [3]) have been constructed in recent years, managing large-scale and real-world facts as a graph [4]. In such graphs, each node represents an entity with attributes, and each edge denotes a relationship between two entities. Answering Graph Query on Knowledge Graphs: Querying knowledge graphs is essential for a wide range of applications, e.g., question answering and semantic search [5]. For example, consider that a user wants to find all cars produced in Germany . One can come up with a reasonable graph representation of this query as a query graph G Q , and identify the exact or approximate matches of G Q in a knowledge graph G using graph query models [6]–[10]. Correct answers can be