A LOCATION AND DIVERSITY-AWARE OPTIMIZED NEWS FEED SYSTEM FOR ANDROID USERS

Abstract

A location aware news feed system generates news feeds for a mobile user based on her spatial preference and non-spatial preference. Existing LANF systems simply send the most relevant geo-tagged messages to their users. Diversity is a very important feature for location-aware news feeds because it helps users discover new places and activities. In this paper, D-MobiFeed; a new LANF system is proposed which enables a user to specify the minimum number of message categories ( h ) for the messages in a news feed. In D-MobiFeed, our objective is to efficiently schedule news feeds for a mobile user at his/her current and predicted locations, such that (i) each news feed contains messages belonging to at least h different categories, and (ii) their total relevance to the user is maximized. New feed system uses Maximum Likelihood Algorithm to predict future location of user and most relevant messages are retrieve using semantic ontology.