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Point-of-Interest (POI) Recommendation for Location Based Services

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Document pages: 6 pages

Abstract: The research focuses on the location data of user to make meaningful and good quality recommendation of Point-of-interest in real world based on geographical influence. Point-of-interest recommendation is an emerging area of research on location-based social networks (LBSNs). Geographical proximity, a unique feature of LBSNs can acts as major factor which significantly affects users’ check-in behaviour. Location-based social networks made it viable for servers to record users’ location periodically over time, extract their mobility patterns and deduce individual precedence. As a crucial unit of LBSNs, recommender systems gained popularity in recent years. Recommender systems acts as a content filtering systems which can automatically present a list of more suitable candidate locations from available corpus of POI for users based on their preferences, which is distinct from traditional search methods in which user explicitly needs to search of a particular poi based on users’ requirement. This paper proposes a solution for POI recommendation incorporating temporal and social influential factor with GA-GMM model.

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