Results 1 to 10 of about 213 (111)
Implications of a Twitter data-centred methodology for assessing commuters’ perceptions of the Delhi metro in India [PDF]
Computational Urban Science, 2022 Owing to the onset of the new media age, the idea of e-public participation has proven to be a great complement to the limitations of the conventional public participation approach. In this respect, location-based social networks (LBSN) data can prove to
Apoorv Agrawal, Paulose N. Kuriakose
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ISPRS International Journal of Geo-Information, 2020 Location-based social networks (LBSNs) have rapidly prevailed in China with the increase in smart devices use, which has provided a wide range of opportunities to analyze urban behavior in terms of the use of LBSNs.
Muhammad Rizwan +2 more
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P3OI-MELSH: Privacy Protection Target Point of Interest Recommendation Algorithm Based on Multi-Exploring Locality Sensitive Hashing [PDF]
Frontiers in Neurorobotics, 2021 With the rapid development of social network, intelligent terminal and automatic positioning technology, location-based social network (LBSN) service has become an important and valuable application. Point of interest (POI) recommendation is an important
Desheng Liu +5 more
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IIMB Management Review, 2016 Recommender 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.
Murale Narayanan +1 more
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Points-of-Interest Recommendation Algorithm Based on LBSN in Edge Computing Environment
IEEE Access, 2020 With the advancement of the Internet of Everything era and the popularity of mobile devices, Location-based Social Networks (LBSN) have penetrated people's lives.
Keyan Cao, Jingjing Guo, Yefan Liu
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POI recommendation method using LSTM-attention in LBSN considering privacy protection
Complex & Intelligent Systems, 2021 Aiming at the problems of traditional point of interest (POI), such as sparse data, lack of negative feedback, and dynamic and periodic changes of user preferences, a POI recommendation method using deep learning in location-based social networks (LBSN ...
Kun Wang, Xiaofeng Wang, Xuan Lu
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Time Aware Point-of-interest Recommendation [PDF]
Jisuanji kexue, 2021 In location-based social networks (LBSN),users share their location and content related to location information.Point-of-interest (POI) recommendation is an important application in LBSN which recommends locations that might be of interest to users ...
WANG Ying-li, JIANG Cong-cong, FENG Xiao-nian, QIAN Tie-yun
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ISPRS International Journal of Geo-Information, 2023 In recent years, next location prediction has been of paramount importance for a wide range of location-based social network (LBSN) services. The influence of geographical and temporal contextual information (GTCI) is crucial for analyzing individual ...
Fatemeh Ghanaati +2 more
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DYNAMIC TRIP ATTRACTION ESTIMATION WITH LOCATION BASED SOCIAL NETWORK DATA BALANCING BETWEEN TIME OF DAY VARIATIONS AND ZONAL DIFFERENCES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 The emergence of location based social network (LBSN) services make it accessible and affordable to study individuals’ mobility patterns in a fine-grained level.
N. W. Hu, P. J. Jin
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A Survey of Studies on Deep Learning Applications in POI Recommendation [PDF]
Jisuanji gongcheng, 2022 In Location-Based Social Network(LBSN), users conduct check-ins at selected Point of Interest(POI) to record their trajectories, share feelings with their friends and form social friends.POI recommendation is an important service of LBSN to help users ...
TANG Jiaxin, CHEN Yang, ZHOU Mengying, WANG Xin
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