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GeoTense: Spotting Patterns in Geo-Social Networks with Tensors [PDF]
, 2015 Faloutsos, Christos +2 more
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HMGCL: Heterogeneous multigraph contrastive learning for LBSN friend recommendation
World Wide Web, 2022Yongkang Li, Zipei Fan, Du Yin
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Using Visualization to Explore Original and Anonymized LBSN Data
Computer Graphics Forum, 2016AbstractWe present GSUVis, a visualization tool designed to provide better understanding of location‐based social network (LBSN) data. LBSN data is one of the most important sources of information for transportation, marketing, health, and public safety.
E. Tarameshloo +3 more
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Personalized LBSN Recommendation System
Proceedings of the 2017 International Conference on Management Engineering, Software Engineering and Service Sciences, 2017To explore deep value of user comments in LBSN, this article through to Foursquare check-in with geography information analysis and review data using AFINN dictionary user comments emotions tend to get user implicit rating for this product. Using the score as the foundation, proposed and implemented an integrated collaborative filtering recommendation ...
Jingling Zhao +3 more
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LocRec: Rule-Based Successive Location Recommendation in LBSN
2018 IEEE International Conference on Communications (ICC), 2018Successive location recommendation has recently emerged as an important service in Location-Based Social Networks (LBSNs). It aims at recommending the next location(s) to visit to a user given its current and previous locations. Although several recommenders have been proposed, only few works have considered the sequential correlations among locations ...
Hanane Amirat +3 more
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Community Detection and Location Recommendation Based on LBSN
2017 International Conference on Network and Information Systems for Computers (ICNISC), 2017Community detection is an effective tool for mining hidden information in social networks. Label propagation is a widely used and effective community detection algorithm. A lot of work has been done based on label propagation for standalone machine computing. While in location based social networks (LBSN), paralleled label propagation is needed to deal
Chang Su +3 more
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Meta Path-Aware Recommendation Method Based on Non-Negative Matrix Factorization in LBSN
IEEE Transactions on Network and Service Management, 2022Location-based social networks (LBSN) is a new type of heterogeneous information network (HIN). The check-in data usually has the characteristics of a large amount of data and high sparsity.
Ze Wang, Wenju Liu, Shimin Sun
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Point-of-Interest Recommendation Based on Spatial Clustering in LBSN
2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC), 2018In location-based social networks, many studies have been put into forward to improve point-of-interest (POI) recommendation, according to the users' historical check-ins and context aware information. But the spatial distribution feature of the users' check-in has not been well studied.
Chang Su, Ning Li, Xian-Zhong Xie
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Location-Time-Sociality Aware Personalized Tourist Attraction Recommendation in LBSN
2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design ((CSCWD)), 2018With the development of the tourism, vast amount of tourist attraction information makes it complex and time-consuming for users to obtain satisfactory travel destination. Rich topological, temporal and spatial information in Location-Based Social Network (LBSN) helps to mine user preference deeply and evokes effectiveness of tourist attraction ...
Ziqing Zhu, Jiuxin Cao, Chenghao Weng
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