Results 1 to 10 of about 817 (198)
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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A study and analysis of recommendation systems for location-based social network (LBSN) with big data [PDF]
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.
Aswani Kumar Cherukuri, Murale Narayanan
exaly +4 more sources
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
doaj +2 more sources
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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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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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.
Yefan Liu, Keyan Cao, Gongjie Meng
exaly +3 more sources
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 ...
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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ISPRS International Journal of Geo-Information, 2020 The aim of this study is to analyze and compare the patterns of behavior of tourists and residents from Location-Based Social Network (LBSN) data in Shanghai, China using various spatiotemporal analysis techniques at different venue categories. The paper
Naimat Ullah Khan, Wanggen Wan, Shui Yu
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