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.
