Abstract

Abstract:It is extremelywell known to identify hot topics, which can profit numerous undertakingsincluding topic recommendations, the guidance of public opinions, etc. However,in some cases, people may want to know when to re-hot a topic, i.e., make thetopic popular once more.           In thisproject, address this issue by presenting a Spatio-Temporal User TopicParticipation (UTP)                 modelwhich models users behaviors of posting messages. The UTP demonstrate considersclients’ interests, friend-circles, and unexpected events in online socialnetworks. Likewise, it considers the persistent spatio-temporal modeling oftopics, since subjects are changing consistently after some time. Moreover, aweighting plan is proposed to smooth the variances in topic re-hottingprediction. At long last, trial results directed on true informationalcollections exhibit the effectiveness of our proposed models and topicre-hotting prediction techniques.

Keywords:SocialNetworks, User Topic Participation (UTP), Re-hotting Prediction,Spatio-Temporal Model.