Semantic Search for Enterprises Competencies Management

This paper presents a method for semantic search and retrieval in the context of networked enterprises that share services, competencies (knowledge), and a reference ontology (RO). The RO models the universe of domain competencies and is used to build the company profiles starting from their key documents. The search engine is used to identify the competencies needed in a given project. A semantic search engine is capable of representing a user request in terms of the RO concepts and identifying the collection of services or skills (offered by a specific enterprise) that match at best the user request. The proposed semantic search method, referred to as SemSim, is based on concept similarity, derived from the well-known notion of information content. Concepts in the RO are weighted according to a frequency approach. Such weights are used, in our proposal, to derive the pair-wise concept similarity, and an optimized method for computing the similarity of conceptual structures. Finally, we report an experimental assessment where we show that our SemSim method performs better than some of the most representative similarity search methods defined in the literature.