Results 11 to 20 of about 255,061 (262)
Exploiting Spatial and Temporal for Point of Interest Recommendation
An increasing number of users have been attracted by location-based social networks (LBSNs) in recent years. Meanwhile, user-generated content in online LBSNs like spatial, temporal, and social information provides an ever-increasing chance to study the ...
Jinpeng Chen +5 more
doaj +3 more sources
Contextualized Point-of-Interest Recommendation [PDF]
Point-of-interest (POI) recommendation has become an increasingly important sub-field of recommendation system research. Previous methods employ various assumptions to exploit the contextual information for improving the recommendation accuracy. The common property among them is that similar users are more likely to visit similar POIs and similar POIs ...
Peng Han 0005 +6 more
openaire +1 more source
On recommendation problems beyond points of interest [PDF]
Recommendation systems aim to recommend items or packages of items that are likely to be of interest to users. Previous work on recommendation systems has mostly focused on recommending points of interest (POI), to identify and suggest top-k items or packages that meet selection criteria and satisfy compatibility constraints on items in a package ...
Ting Deng, Wenfei Fan, Floris Geerts
openaire +3 more sources
Review Recommendation for Points of Interest's Owners [PDF]
Websites that provide reviews for services and products deal with big volumes of data (many users writing many reviews for many items). Then, recommendation algorithms come to the rescue in matching reviews to the consumers who are reading them. Such online review applications usually recommend the most useful reviews for consumers to read.
Thiago R. P. Prado, Mirella M. Moro
openaire +2 more sources
Point-of-interest lists and their potential in recommendation systems [PDF]
Location based social networks, such as Foursquare and Yelp, have inspired the development of novel recommendation systems due to the massive volume and multiple types of data that their users generate on a daily basis. More recently, research studies have been focusing on utilizing structural data from these networks that relate the various entities ...
Giorgos Stamatelatos +4 more
openaire +2 more sources
Techniques for Improving Performance of Recommender Systems for Tourist Point of Interest Recommendation [PDF]
Among the various applications of recommender systems, their use in estimating and suggesting points of interest (POIs) for tourists has expanded significantly in recent years.
Samaneh Sheibani +2 more
doaj +1 more source
Point-of-interest (POI) recommendation has been well studied in recent years. However, most of the existing methods focus on the recommendation scenarios where users can provide explicit feedback. In most cases, however, the feedback is not explicit, but
Lei Guo +3 more
doaj +1 more source
Influence-Aware Successive Point-of-Interest Recommendation
AbstractIn recent years, with the rapid development of mobile applications, user check-in histories have been increasing. Successive point-of-interest (POI) recommendation has gained growing attention. Existing successive point-of-interest recommendation methods learn long- and short-term user preferences through historical check-in sequences to ...
Xinghe Cheng +4 more
openaire +2 more sources
Survey on Next Point-of-Interest Recommendation Algorithms [PDF]
With the rapid development of mobile Internet and location-based services, location-based social networks have become an integral part of users?? daily lives.
LIU Guangteng, WANG Feng, WU Zhongbo
doaj +1 more source
Adversarial Point-of-Interest Recommendation
Point-of-interest (POI) recommendation is essential to a variety of services for both users and business. An extensive number of models have been developed to improve the recommendation performance by exploiting various characteristics and relations among POIs (e.g., spatio-temporal, social, etc.).
Fan Zhou 0002 +5 more
openaire +2 more sources

