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DESCRIPTION:Click for Latest Location Information: http://semtechbizsf2012.semanticweb.com/sessionPop.cfm?confid=65&proposalid=4617\nMost social media sites are organized around tags, user-contributed folksonomies. Although tags organize large collections quickly, systems know nothing about what tags mean, and can't do reasoning based on the meaning of tags.\n \nXen's knowledge base is derived from Linked Data sources such as Freebase and DBpedia and contains more than 20 million interests. Xen combines this knowledge base with interests volunteered by users, discovered through user behaviors, and mined from text.\nOur rich knowledge base extends the value of social data, as it starts out understanding relationships between interests that collaborative filtering systems need to discover at great cost. Semantic knowledge helps Xen find relevant content for users. Our partners benefit from our recommendation technology and gain unprecedented insight into the interests of their users.\nIn this presentation, Xen will demonstrate how our platform blends Linked Data with interests inferred from social data to generate relevant recommendations for users.\n \nTopics:\n? Integrating semantic data into a social media platform\n? Text analysis of social media content\n? Semantic inference to support recommendations\n? Intelligent creation of user-controllable interest graphs\n? Emerging ecosystems around the interest graph
DTSTART:20120605T134500
SUMMARY:Xen: Blending Semantic and Social Data for Personalization
DTEND:20120605T142959
LOCATION: See Description
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