TeCre: A Novel Temporal Conflict Resolution Method Based on Temporal Knowledge Graph Embedding

Since the facts in knowledge graph (KG) cannot be updated automatically over time, some have temporal conflicts. To discover and eliminate conflicts KG, this paper proposes a novel conflict resolution method based on KG embedding (named TeCre). Firstly, predicate relation timestamp information of time series are incorporated into entity–relation representation by leveraging (KGE) method. Then, taking account chronological sequence evolution TeCre constrains according to principles disjoint, precedence, mutually exclusive constraints. Besides that, further considers vectorization KG. Finally, facts, deletes tail entities employs link prediction complete missing output score function embedding. Experimental results four public datasets show that is significantly better than state-of-the-art model. The mean reciprocal ranking (MRR) Hits@10 at least 5.46% 3.2% higher baseline methods, respectively.