Knowledge Graph Completion for Activity Recommendation in Business Process Modeling

Abstract Activity recommendation is an approach to assist process modelers by recommending suitable activities to be inserted at a user-defined position. In this paper, we suggest approaching activity recommendation as a knowledge graph completion task. We convert business process models into knowledge graphs through various translation methods and apply embedding- and rule-based knowledge graph completion techniques to the translated models. Our experimental evaluation reveals that generic knowledge graph completion methods do not perform well on the given task. They lack the flexibility to capture complex regularities that can be learned using a rule-based approach specifically designed for activity recommendation.