Logical reasoning over knowledge graphs in vector space

Abstract

Due to the incompleteness of knowledge map, the existing knowledge map is usually missing, and the task of knowledge reasoning is to predict the missing facts according to a large number of information such as entities and relationships. In order to satisfy the interpretability and accuracy, this paper proposes a multi-hop reasoning method combining first-order logic and graph embedded vector, which has the mathematical rigor of logical reasoning and the high accuracy of embedded vector. For the specified query, it is transformed into a first-order logical operation representation, and the query dependency graph is instantiated, and the reverse sampling from the root node to the anchor point in the instantiation process ensures that the query must have an answer. According to the query calculation diagram combined with logical operators, reasoning is based on embedded method, which avoids explicitly traversing KG and obtains the query answer.