Abstract
Point-of-Interest (POI) recommendation helps to find new places for users to
visit, along with the popularity of locations. Recommendation of POI is the most
important in location-based social networks (LBSNs). This paper discusses different
parameters that significantly impact the POI recommendation process and make the
prediction much more accurate. A comprehensive review of a few research works and
the methodologies employed for POI recommendation have been presented. POI
recommendation techniques have been classified based on many, such as the interest of
the tourist in particular POI, popularity of the POI, weather conditions, etc. A summary
of related research work is presented for each category, along with their respective
drawbacks. Finally, the possible directions toward future work in this area are included,
along with the conclusion.
Keywords: Check-in, Point-of-Interest, Popularity, Recommendation, User interest, Weather details.
Related Journals
Recent Patents on Computer Science
The Chinese Journal of Artificial Intelligence
Current Chinese Computer Science
Journal of Fuzzy Logic and Modeling in Engineering
Recent Advances in Computer Science and Communications
International Journal of Sensors, Wireless Communications and Control
Journal of Intelligent Systems in Current Computer Engineering
Current E-Learning
Current Computer Science
Wireless and Communication Letters
Related Books
Computational Intelligence For Data Analysis
Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
A First Course in Artificial Intelligence
Artificial Intelligence: Models, Algorithms and Applications
Advanced Computing Techniques: Implementation, Informatics and Emerging Technologies
Handbook of Mobile Application Development: A Guide to Selecting the Right Engineering and Quality Features
Applications of Modern High Performance Networks
Arduino Meets Matlab: Interfacing, Programs and Simulink
Arduino and SCILAB based Projects
Application of Chaos and Fractals to Computer Vision