LEARNING BEYOND SOCIAL NETWORKING: RECOMMENDATION FUTURE INTERESTS IN TECHNICAL MICROBLOGGING TRACES

Abstract

Microblogging offers portable, organic and fastinformation worldwide. However, its contents have not beenyet studied in self-learning strategies. This paper aims todiscuss effective learning in microblogging, by means of aweb open source robot that will provide users’ future lifestream, social networking graphs and tag cloud statistics.Using Bayesian Algorithms, the system will trace users’information,, predict their future learninginterests/people/groups and send them back arecommendation. The recommendation is traced and user’sactions are evaluated towards their knowledge optimizationstrategies.Index Terms ⎯ Microblogging, Web search,Recommendation System, Bayesian Algorithms.