Results 241 to 250 of about 852,574 (290)

Behavior-based location recommendation on location-based social networks

GeoInformatica, 2017
Location recommendation makes suggestions of nearby locations based on user’s locational preferences and spatial movement patterns. In this paper, we propose two novel location recommendation methods called Behavior Factorization (BF) and Latent Behavior Analysis (LBA).
Seyyed Mohammadreza Rahimi, Xin Wang, Behrouz Far   +2 more
openaire   +1 more source

A Mobile Location-Aware Recommendation System

Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, 2014
Improvements in mobile technology provide greater personal information accessibility, data incorporation, and public resources accessibility, “anytime, anywhere”. Smartphones are not only devices that make phone calls, but have also become a gateway to the Internet. Mobile devices offer the capabilities of usage flexibility, mobility, fast wireless
UTKU, SEMİH, Atay, Canan Eren
openaire   +2 more sources

Personalized Location Recommendation System Personalized Location Recommendation System

International Journal of Applied Evolutionary Computation, 2019
Location acquisition and wireless communication technologies are growing in location-based social networks. With the rapid development of location-based social networks (LBSNs), location recommendation has become an important for helping users to discover interesting locations.
openaire   +1 more source

Personalized location recommendation on location-based social networks

Proceedings of the 8th ACM Conference on Recommender systems, 2014
Personalized location recommendation is a special topic of recommendation. It is related to human mobile behavior in the real world regarding various contexts including spatial, temporal, social, and content. The development of this topic is subject to the availability of human mobile data.
Huiji Gao, Jiliang Tang, Huan Liu
openaire   +1 more source

Personalized location recommendation for location-based social networks

2017 IEEE/CIC International Conference on Communications in China (ICCC), 2017
With the development of social networks and wireless communication technology, location-based social networks (LBSNs) are developing rapidly. Personalized location service in location-based social networks can provide users with a new point-of-interest (POI). Compared to traditional recommendation, point-of-interest recommendation integrates the social
Qianfang Xu, Jiachun Wang, Bo Xiao
openaire   +1 more source

Personalized location aware recommendation system

2015 International Conference on Advanced Computing and Communication Systems, 2015
A Personalized location aware recommendation system has been designed and evaluated in this paper. The idea is to infer user's preferences and thus to recommend nearby locations such as hospitals, food courts, shopping and so on. User's current search contexts are rarely considered by the well known location recommendation system named FOURSQUARE ...
K. Veningston, R. Shanmugalakshmi
openaire   +1 more source

Recommendations-based location privacy control

2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), 2013
In this paper, we propose and investigate a user-centric device-cloud architecture for intelligently managing user data. The architecture allows users to keep their (private) data on their mobile devices and decide what to share with the service providers on the cloud, based on their individual privacy preferences, in order to get personalized services.
null Hongxia Jin, Gokay Saldamli, Richard Chow, Bart P. Knijnenburg   +3 more
openaire   +1 more source

Mobile Location-Based Recommender

2011
Mobile devices, including cell phones, capable of geo-positioning (or localization) are paving the way for new computer assisted systems called mobile location-based recommenders (MLBRs). MLBRs are systems that combine information on user’s location with information about user’s interests and requests to provide recommendations that are based on ...
Mahsa Ghafourian, Hassan A. Karimi
openaire   +1 more source

Privacy Preserving Location Recommendations

2017
With the rapid development of location based social networks (LBSN) and location based services (LBS), the location recommendation to users has gained much attentions. A traditional location recommendation scheme may use any of the following information to generate a location recommendation: users’ check-in frequencies on different locations, their ...
Shahriar Badsha, Xun Yi, Ibrahim Khalil, Dongxi Liu, Surya Nepal, Elisa Bertino   +5 more
openaire   +1 more source

Location Recommendation with Privacy Protection

Proceedings of the 2019 3rd International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence, 2019
With the development of Internet technology, users pay more and more attention to the privacy of personal location data. In order to cover up the user's original check-in data information and prevent attackers from using the user's friend relationship to infer the privacy information of a single user, our paper proposed a hybrid privacy protection ...
Chang Su, Yumeng Chen, Xianzhong Xie
openaire   +1 more source