Results 21 to 30 of about 3,208 (177)
Concurrency and Computation: Practice and Experience, Volume 34, Issue 15, 10 July 2022., 2022 Abstract Today, millions of active users spend a percentage of their time on location‐based social networks like Yelp and Gowalla and share their rich information. They can easily learn about their friends' behaviors and where they are visiting and be influenced by their style.
Sadaf Safavi, Mehrdad Jalali
wiley +1 more source
A topological model of trajectories with road network space
Transactions in GIS, Volume 26, Issue 4, Page 1847-1878, June 2022., 2022 Abstract Spatiotemporal topological semantic information has attracted a lot of attention recently when exploring high‐level human movement features in geographic contexts. Although topological semantics between a trajectory and individual spatial objects have been studied extensively, few studies have focused on movements in the specific context of ...
Tao Wu +4 more
wiley +1 more source
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
doaj +1 more source
Research on the Prediction System of Event Attendance in an Event‐Based Social Network
Wireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022 In recent years, an event‐based social network recommendation system has attracted more and more researchers’ attention. Most EBSN recommendation systems mainly focus on recommending events to users. However, in many daily activities, it is necessary to accurately estimate the number of event participants for EBSN event organizers.
Tianming Lan +4 more
wiley +1 more source
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
doaj +1 more source
Wireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022 There exist various challenges introduced by a large number of multimedia photos and videos for personalized travel recommendation in the era of big data. In order to resolve such challenges, a context‐aware personalized travel recommendation system based on data mining is proposed in this study.
Jiangong Lian +2 more
wiley +1 more source
INTRA-URBAN MOVEMENT FLOW ESTIMATION USING LOCATION BASED SOCIAL NETWORKING DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook, which have attracted an increasing number of users and greatly enriched their urban experience.
A. Kheiri, F. Karimipour, M. Forghani
doaj +1 more source
Computational Intelligence and Neuroscience, Volume 2022, Issue 1, 2022., 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 ...
Hidayat Ullah +5 more
wiley +1 more source
ISPRS International Journal of Geo-Information, 2020 The aim of the current study is to analyze and extract the useful patterns from Location-Based Social Network (LBSN) data in Shanghai, China, using different temporal and spatial analysis techniques, along with specific check-in venue categories.
Naimat Ullah Khan, Wanggen Wan, Shui Yu
doaj +1 more source
A hybrid analysis of LBSN data to early detect anomalies in crowd dynamics [PDF]
Future generations computer systems, 2020 Undoubtedly, Location-based Social Networks (LBSNs) provide an interesting source of geo-located data that we have previously used to obtain patterns of the dynamics of crowds throughout urban areas.
R. Redondo +4 more
semanticscholar +1 more source