Knowledge and experience management integration: A graph-based learning approach

In order to efficiently and easily manage knowledge within Small and Medium-sized Enterprises (SMEs), Personal Knowledge Management systems (PKMs) can be used. They enable individuals to formalize their experiences and knowledge using knowledge graphs called Personal Knowledge Graphs (PKG). To facilitate the sharing and dissemination of these individual knowledge repositories, an Organizational Knowledge Management system (OKMs) enables to gather several pieces of individual experiences or knowledge within Organizational Knowledge Graphs (OKG). This article proposes an approach for knowledge formalization and exploitation where graph nodes are transformed into vector embeddings and a learning mechanism enables to enrich them by the knowledge of their neighbors. Based on knowledge formalized by vectors, a second mechanism enables to identify relevant pieces of knowledge according to a new request. We applied our proposals in industrial problem-solving domain to recommend actors likely to work on new problems based on their fields of competence and their experiences. Our experiments show that it is possible to make better actor recommendations for new problems by reinforcing the knowledge of these actors through learning with knowledge that are semantically similar to that of the new problems.