Knowledge Graph Query and Reasoning Based on Game Theory
Hu Xueruobai, Huang J. Jie, Jiantao Wang, Qin Xin · 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE) · 2019
Aiming at the problem of sparse information distribution and lack of good correlation between data in the era of big data, this paper proposes a knowledge graph query and reasoning method based on game theory. This method first establishes the domain ontology model according to the domain requirements, and establishes the domain knowledge graph according to the modified model, and then uses the PageRank algorithm to evaluate the value of each node in the knowledge graph, and then conducts the knowledge graph query based on the game thinking orientation and the talent recommendation system as an example. This method makes use of the relationship between knowledge and nodes in the knowledge graph and realizes the effective talent recommendation.