Enterprise Wisdom Captured Socially

Data availability in online social networks as well as the business world has lately not been an issue. Vast amounts of data are being generated by social networking users in the form of informal interactions. What has been an issue, is the transformation of data into useful information, that in time and with appropriate processing becomes knowledge. In this paper we examine knowledge generation under informal social communications, based on semantically enriched user-generated data and associated metadata. We dynamically capture users' interests and expertise using such semantically enriched content. Knowledge networks of users emerge, exhibiting collective intelligence. To capture such collective knowledge, we propose a novel knowledge base paradigm, which seamlessly integrates information from multiple platforms and facilitates knowledge extraction, mining, discovery and inferencing. Using semantically enriched user profiles, we compute semantic similarity between users and content in a joint semantic space, driving numerous applications.

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