
Currently a day's social media becomes fashionable. We tend to sit down with these social networks involving geographical data as location-based social networks (LBSNs). Such data brings opportunities and challenges for recommender systems to unravel the cold begin, meagerness downside of datasets and rating prediction. During this paper, we tend to alter use of the mobile users' location sensitive characteristics to hold out rating postulation.
The connection between user's ratings and user-item geographical location distances, known as user-item geographical affiliation, the connection between users' rating variations and user-user geographical location distances, known as user-user geographical affiliation. Paper, we've got a bent to change use of the mobile users' location sensitive characteristics to hold out rating declaration.
by Prof. Brijendra Gupta | Shreyas Walujkar | Vishal Dhane | Moreshwar Tendulkar | Tushar Jadhav"Recommendation by Service Rating Using GPS for Mobile Users"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017,
URL: http://www.ijtsrd.com/papers/ijtsrd7167.pdf
Direct Link - http://www.ijtsrd.com/engineering/computer-engineering/7167/recommendation-by-service-rating-using-gps-for-mobile-users/prof-brijendra-gupta
Computer Engineering, Call For Paper
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