Abstract：The reasoning ability of most existing dynamic knowledge map reasoning methods under the same time and multiple relationships is limited . Aiming at this problem, a method of dynamic knowledge graph inference based on multi-relational cyclic events(Multi-Net) is proposed. The improved multi-relational proximity aggregator is employed to fuse target entity neighborhood information to obtain more accurate representation of entity neighborhood vector, and Multi-Net is simplified by optimizing information fusion, and the ability to handle the conflict of relations between two entities in a specific scope is improved by adding the relationship prediction task to Multi-Net. Experiments of entity prediction and relationship prediction on large real datasets indicate that Multi-Net improves the reasoning ability of dynamic knowledge maps effectively.
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