Results 31 to 40 of about 200 (160)

SSTP: Social and Spatial-Temporal Aware Next Point-of-Interest Recommendation

Data Science and Engineering, 2023
The expansion of available information in location-based social networks (LBSNs) has led to information overload, making it urgent to discover users’ next point-of-interest (POI).
Junzhuang Wu, Yujing Zhang, Yuhua Li, Yixiong Zou, Ruixuan Li, Zhenyu Zhang   +5 more
doaj   +1 more source

The Geography of Social Media Data in Urban Areas: Representativeness and Complementarity

ISPRS International Journal of Geo-Information, 2021
This research sheds light on the relationship between the presence of location-based social network (LBSN) data and other economic and demographic variables in the city of Valencia (Spain). For that purpose, a comparison is made between location patterns
Álvaro Bernabeu-Bautista, Leticia Serrano-Estrada, V. Raul Perez-Sanchez, Pablo Martí   +3 more
doaj   +1 more source

A study and analysis of recommendation systems for location-based social network (LBSN) with big data

IIMB Management Review, 2016
AbstractRecommender systems play an important role in our day-to-day life. A recommender system automatically suggests an item to a user that he/she might be interested in. Small-scale datasets are used to provide recommendations based on location, but in real time, the volume of data is large.
Narayanan, Murale, Cherukuri, Aswani Kumar   +1 more
openaire   +3 more sources

NPR-LBN: next point of interest recommendation using large bipartite networks with edge and cloud computing

Journal of Cloud Computing: Advances, Systems and Applications, 2023
During the last decades, tourism has been augmented worldwide through which the diversity of tourists’ interests is increased and is challenging to tackle with the traditional management system.
Inayat Khan, Anwar Sadad, Gauhar Ali, Mohammed ElAffendi, Razaullah Khan, Tariq Sadad   +5 more
doaj   +1 more source

Event-Based Probabilistic Embedding for POI Recommendation

Applied Sciences, 2023
Location-based social networks (LBSNs) have collected massive geo-tagged information, enabling the derivation of user preference for point of interests (POIs) in support of personalized recommendation. The existing embedding techniques deal with multiple
Tiancheng Zhang, Hengyu Liu, Xue Geng, Ge Yu   +3 more
doaj   +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

Hybrid Model for Point-of-Interests Recommendation Based on Time Effect [PDF]

Jisuanji gongcheng, 2019
In Location-Based Social Networks(LBSNs),real-time recommendation data of Point-of-Interests(POIs) and check-in data of users are highly sparse.Therefore,a hybrid recommendation model based on time effect is proposed.Through the data model of potential ...
ZHANG Qishan, LI Ke, LIN Xiaorong
doaj   +1 more source

Improving Destination Choice Modeling Using Location-Based Big Data

ISPRS International Journal of Geo-Information, 2017
Citizens are increasingly sharing their location and movements through “check-ins” on location based social networks (LBSNs). These services are collecting unprecedented amounts of big data that can be used to study how we travel and interact with our ...
Joseph Molloy, Rolf Moeckel
doaj   +1 more source

An Automatic Annotation Method for Discovering Semantic Information of Geographical Locations from Location-Based Social Networks

ISPRS International Journal of Geo-Information, 2019
Location-Based Social Networks (LBSNs) contain rich information that can be used to identify and annotate points of interest (POIs). Discovering these POIs and annotating them with this information is not only helpful for understanding the social ...
Zhiqiang Zou, Xu He, A-Xing Zhu
doaj   +1 more source

Exploring the Social Implications of Location Based Social Networking: An Inquiry into the Perceived Positive and Negative Impacts of Using LBSN between Friends

2010 Ninth International Conference on Mobile Business and 2010 Ninth Global Mobility Roundtable (ICMB-GMR), 2010
Location based social networking (LBSN) applications are part of a new suite of emerging social networking tools that run on the Web 2.0 platform. LBSN is the convergence between location based services (LBS) and online social networking (OSN). LBSN applications offer users the ability to look up the location of another “friend” remotely using a smart ...
Sarah Jean Fusco, Katina Michael, M.G. Michael, Roba Abbas   +3 more
openaire   +2 more sources