Abstract: Social networking tools, blogs and microblogs, user-generated content sites, discussion groups, problem reporting, and other social services have transformed the way people communicate and consume information. Yet managing this information is still a very onerous activity for both the consumer and the provider, the information itself remains passive. Traditional methods of keyword extraction from text based on predefined codified knowledge are not well suited for use in such empirical environments, and as such do little to support making this information more an active part of the processes to which it may otherwise belong. In this paper we analyse various use cases of real-time context-sensitive keyword detection methods using IBM LanguageWare? applications as example. We present a general high-performance method for exploiting ontologies to automatically generate semantic metadata for text assets, and demonstrate examples of how this method can be implemented to bring commercial and social benefits. In particular, we overview metadata-driven semantic publishing on the BBC FIFA World Cup 2010 website and the applications for social semantic desktops.

Keywords:data mining, natural language processing, recommender systems, social semantic web, graph-based methods.

ACM Classification Keywords: H.3.4 Information Storage and Retrieval: Systems and Software – information networks; H.3.5 Information Storage and Retrieval: Online Information Services – data sharing.

Link:

APPLICATION OF SOCIAL ANALYTICS FOR BUSINESS INFORMATION SYSTEMS

Alexander Troussov, D.J. McCloskey?

http://www.foibg.com/ibs_isc/ibs-26/ibs-26-p02.pdf