DC proposal
Hasti Ziaimatin · International Semantic Web Conference · 2011
Expertise modeling has been the subject of extensive research in two main disciplines - Information Retrieval (IR) and Social Network Analysis (SNA). Both IR and SNA techniques build the expertise model through a document-centric approach providing a macro-perspective on the knowledge emerging from large corpus of static documents. With the emergence of the Web of Data, there has been a significant shift from static to evolving documents, characterized by micro-contributions. Thus, the existing macroperspective is no longer sufficient to track the evolution of both knowledge and expertise. The aim of this research is to provide an all-encompassing, domainagnostic model for expertise profiling in the context of dynamic, living documents and evolving knowledge bases. Our approach combines: (i) finegrained provenance, (ii) weighted mappings of Linked Data concepts to expertise profiles, via the application of IR-inspired techniques on microcontributions, and (iii) collaboration networks - to create and enrich expertise profiles in community-centered environments.