Results 31 to 40 of about 1,139,810 (293)

Time-aware point-of-interest recommendation

Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval, 2013
The availability of user check-in data in large volume from the rapid growing location based social networks (LBSNs) enables many important location-aware services to users. Point-of-interest (POI) recommendation is one of such services, which is to recommend places where users have not visited before. Several techniques have been recently proposed for
Yuan, Quan, Cong, Gao, Ma, Zongyang, Sun, Aixin, Thalmann, Nadia Magnenat   +4 more
openaire   +2 more sources

A Point-of-Interest Recommendation Method Exploiting Sequential, Category and Geographical Influence

ISPRS International Journal of Geo-Information, 2022
Point of interest (POI) recommendation as an important service in location-based social networks has developed rapidly, which can help users find more interesting unknown locations and facilitate service providers to provide users with more accurate ...
Xican Wang, Yanheng Liu, Xu Zhou, Xueying Wang, Zhaoqi Leng   +4 more
doaj   +1 more source

Review Recommendation for Points of Interest's Owners [PDF]

Proceedings of the 28th ACM Conference on Hypertext and Social Media, 2017
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   +1 more source

RecPOID: POI Recommendation with Friendship Aware and Deep CNN

Future Internet, 2021
In location-based social networks (LBSNs), exploit several key features of points-of-interest (POIs) and users on precise POI recommendation be significant. In this work, a novel POI recommendation pipeline based on the convolutional neural network named
Sadaf Safavi, Mehrdad Jalali
doaj   +1 more source

A Personalised Ranking Framework with Multiple Sampling Criteria for Venue Recommendation [PDF]

, 2017
Recommending a ranked list of interesting venues to users based on their preferences has become a key functionality in Location-Based Social Networks (LBSNs) such as Yelp and Gowalla.
Burges Christopher J., Cheng Chen, Manotumruksa Jarana, Rendle Steffen, Yuan Fajie   +4 more
core   +1 more source

Exploiting Spatial and Temporal for Point of Interest Recommendation

Complexity, 2018
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, Wen Zhang, Pei Zhang, Pinguang Ying, Kun Niu, Ming Zou   +5 more
doaj   +1 more source

A Spatiotemporal Dilated Convolutional Generative Network for Point-Of-Interest Recommendation

ISPRS International Journal of Geo-Information, 2020
With the growing popularity of location-based social media applications, point-of-interest (POI) recommendation has become important in recent years. Several techniques, especially the collaborative filtering (CF), Markov chain (MC), and recurrent neural
Chunyang Liu, Jiping Liu, Shenghua Xu, Jian Wang, Chao Liu, Tianyang Chen, Tao Jiang   +6 more
doaj   +1 more source

How can we create a recommender system for tourism? A location centric spatial binning-based methodology using social networks

International Journal of Information Management Data Insights, 2023
Point of Interest (POI) recommendation is an important Location-Based Social Network (LBSN) task that has become a hotspot in the past decade. It aims to exploit the user's preferences for venues and recommend the POIs for their next visit.
Malika Acharya, Shilpi Yadav, Krishna Kumar Mohbey   +2 more
doaj   +1 more source

Beyond Personalization: Research Directions in Multistakeholder Recommendation [PDF]

, 2019
Recommender systems are personalized information access applications; they are ubiquitous in today's online environment, and effective at finding items that meet user needs and tastes.
Abdollahpouri, Himan, Adomavicius, Gediminas, Burke, Robin, Guy, Ido, Jannach, Dietmar, Kamishima, Toshihiro, Krasnodebski, Jan, Pizzato, Luiz   +7 more
core   +3 more sources

Point-of-Interest Recommendation

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018
The rapid growth of Location-based Social Networks (LBSNs) provides a great opportunity to satisfy the strong demand for personalized Point-of-Interest (POI) recommendation services. However, with the tremendous increase of users and POIs, POI recommender systems still face several challenging problems: (1) the hardness of modeling non-linear user-POI ...
Ma, Chen, Zhang, Yingxue, Wang, Qinglong, Liu, Xue   +3 more
openaire   +2 more sources