DC Proposal: Capturing Knowledge Evolution and Expertise in Community-Driven Knowledge Curation Platforms
نویسنده
چکیده
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.
منابع مشابه
Expertise Modelling in Community-driven Knowledge Curation Platforms
Expertise modelling 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 signific...
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