Enterprise Collective: Connecting People via Content
Barkol, Omer; Bergman, Ruth; Kasravi, Kas; Golan, Shahar; Risov, Marie
Keyword(s): Text analytics; expert finding; collaboration systems
Abstract: We describe an application for rapidly and optimally responding to enterprise opportunities and challenges, by leveraging the tacit knowledge in an enterprise, via identifying the right subject matter expert(s). Enterprise Collective is a web application that automatically discovers experts and their expertise via semantic analysis of their work products (e.g., e- mails, patents, papers, reports, presentations, and blogs). The key feature of Enterprise Collective is being "passive"; where the employees do not fill out or maintain forms or profiles. The application provides an interactive user interface that hides the underlying complexity. Enterprise Collective can benefit any business user, without extensive training or any analytical background. The application leverages the Expert-Expertise, Expert-Documents, and Expertise-Documents relationships, and subsequently permits navigation within this knowledge space. Enterprise Collective uses technologies for semantic analysis of work products and relevance computation using graph flow. A semi-automatic taxonomy generator is used to extract expertise from documents. The "authority" of each expert in relation to an expertise is computed via the nature of the work product and frequency of references. To demonstrate the benefit of Enterprise Collective in large organization, we describe a case study.
External Posting Date: August 7, 2012 [Fulltext]. Approved for External Publication
Internal Posting Date: August 7, 2012 [Fulltext]