Results 11 to 20 of about 3,208 (177)
Semantic Annotation for Places in LBSN through Graph Embedding [PDF]
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017 With the prevalence of location-based social networks (LBSNs), automated semantic annotation for places plays a critical role in many LBSN-related applications. Although a line of research continues to enhance labeling accuracy, there is still a lot of room for improvement. The crucial problem is to find a high-quality representation for each place. In
Wang, Yan +4 more
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Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets [PDF]
GeoInformatica, 2018 Location-based social networks (LBSN) have provided new possibilities for researchers to gain knowledge about human spatiotemporal behavior, and to make predictions about how people might behave through space and time in the future.
Fan, Hongchao +3 more
core +2 more sources
Ensemble mobility predictor based on random forest and Markovian property using LBSN data
Journal of Internet Services and Applications, 2020 The ubiquitous connectivity of Location-Based Systems (LBS) allows people to share individual location-related data anytime. In this sense, Location-Based Social Networks (LBSN) provides valuable information to be available in large-scale and low-cost ...
Felipe Araújo +5 more
doaj +2 more sources
Personalized Recommendation of Tourist Attractions based on LBSN
DEStech Transactions on Computer Science and Engineering, 2018 Photos metadata in Location-Based Social Networks (LBSN) contain rich time and space information, these metadata provide the basis for the research of personalized recommendation of tourist attractions. The existing methods have many problems such as low accuracy of recommendation and single type of attractions recommendation.
Huifang Lv +4 more
openaire +3 more sources
Improving Location Recommendations Based on LBSN Data Through Data Preprocessing
ElectronicsThe accurate prediction of the next location in a sequence is highly beneficial for users of mobile applications. In this study, we investigate how various data preprocessing techniques affect the performance of location recommendation systems. We utilize datasets from Foursquare and Twitter, incorporating users’ historical check-ins. Key preprocessing
Robert Bembenik +2 more
openaire +2 more sources
Library Book Sharing Network (LBSN)
International Journal of Computer Applications, 2019 This paper consists of all related information of the Library Book Share Network, from perspective of students and librarians. It then explores some of the problems and issues faced by students, if they are unable to find their desired book in their ...
Maham Nasrullah +3 more
openaire +2 more sources
Revisiting city tourism in the longer run: an exploratory analysis based on LBSN data
Current Issues in Tourism, 2023 This study addresses the methodological gap in tourism research regarding the long-term monitoring of tourism activities in urban settings. We propose an analytical framework that uses data from location-based social networks (LBSN) to derive tourists ...
Luis Encalada-Abarca +2 more
semanticscholar +1 more source
UPTDNet: A User Preference Transfer and Drift Network for Cross‐City Next POI Recommendation
International Journal of Intelligent Systems, Volume 2023, Issue 1, 2023., 2023 Cross‐city point of interest (POI) recommendation for tourists in an unfamiliar city has high application value but is challenging due to the data sparsity. Most existing models attempt to alleviate the sparsity problem by learning the user preference transfer and drift.
Taoru Yang +4 more
wiley +1 more source
Where is the consumer centre? A case of St. Petersburg
Regional Science Policy &Practice, Volume 14, Issue 4, Page 916-938, August 2022., 2022 Abstract In an urban economy, the distribution of people and real estate prices depends on the location of the central business district of a city. As distance from the city centre increases, both prices and population density diminish, for travel costs increase in terms of time and money. As manufacturing gradually leaves the cities, the importance of
Konstantin Kholodilin +2 more
wiley +1 more source
Hete-CF: Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations [PDF]
, 2014 Collaborative filtering algorithms haven been widely used in recommender systems. However, they often suffer from the data sparsity and cold start problems.
Luo, Chen, Pang, Wei, Wang, Zhe
core +4 more sources