Eliminating temporal conflicts in uncertain temporal knowledge graphs

In the real world, a majority of facts are not static or immutable but highly ephemeral. Each fact is valid for only a limited amount of time, or it stands in temporal dependencies. In addition, facts with time information are usually accompanied by a real-valued weight which witnesses the possibility of a fact. However, most of existing Knowledge Graphs (KGs) focus on static data thus impeding the comprehensive solution for the management of uncertain and temporal facts in KGs. To fill this gap, we emphasize the characteristics of time and propose a coherent management framework ETC (Eliminate Temporal Conflicts) for temporal consistency. ETC is based on maximum weight clique to detect temporal conflicts in uncertain temporal knowledge graphs and eliminate them to achieve the most probable knowledge graph according to related constraints. Constraint graphs with detailed description have first been proposed to identify temporal constraints for the conflict detection. Also, implicit constraints and weight conversion have been propose for conflict resolution. Experiments over two different temporal knowledge graphs demonstrate the high recall rate and precision rate of our framework