Results 1 to 10 of about 283 (172)
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
exaly +3 more sources
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.
Aswani Kumar Cherukuri +1 more
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
exaly +2 more sources
Social dynamics in cities: analysis through LBSN data
Procedia Computer Science, 2022 Location-Based Social Networks data —LBSN data— reveal, in essence, user preferences and patterns of use of urban space. This information plays a key role in research on social dynamics in cities. Today, social network applications are widely available and this digital data represents a complementary and inescapable source of data for the analysis of ...
Almudena Nolasco-Cirugeda +1 more
exaly +3 more sources
A MAS-Based Approach for POI Group Recommendation in LBSN [PDF]
Lecture Notes in Computer Science, 2020 Location-based recommender systems (LBRS) suggest friends, events, and places considering information about geographical locations. These recommendations can be made to individuals but also to groups of users, which implies satisfying the group as a whole.
Daniela Godoy +2 more
exaly +2 more sources
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
exaly +3 more sources
Understanding the User-Generated Geographic Information by Utilizing Big Data Analytics for Health Care. [PDF]
Comput Intell Neurosci, 2022 There are two main ways to achieve an active lifestyle, the first is to make an effort to exercise and second is to have the activity as part of your daily routine. The study’s major purpose is to examine the influence of various kinds of physical engagements on density dispersion of participants in Shanghai, China, and even prototype check‐in data ...
Ullah H +4 more
europepmc +2 more sources
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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