Knowledge representation and fusion method of human resource-related competitive intelligence

In the big data era, business decision makers pay more attentions on competitive intelligence than ever before. As one of the critical success factors of an enterprise, human resources determine the competitive position in the fierce market environment. Therefore, efficient analysis of human resources-related intelligence seems extremely urgent. This paper attempts to explore a knowledge representation approach for human resource intelligence from the perspective of enterprise resource theory. On one hand, it uses knowledge element model to describe human resource-related intelligence both from the enterprise inside and the competitive environment. On the other hand, a synthetical fusion process based on similarity computing and multi-attribute fusion is designed to further improve the knowledge framework of the collected intelligence, which is seen as the basis of the relation extraction and implicit relation discovery of knowledge element. Experiment results verified the feasibility and validity of this study.