Results 141 to 150 of about 232 (178)

Detecting Overlapping Communities in LBSNs with Enhanced Location Privacy

Proceedings of the Third International Symposium on Women in Computing and Informatics, 2015
Location based social network (LBSNs) for instance Facebook places and Twitter provides large amount of data which allows service providers to create several applications like group marketing, friend and location recommendations, trend inquiry etc. Location based social networks does not provide precise communities which enables users to subscribe ...
K. Sreelekshmi, Pretty Babu
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Personalized POI Recommendation Model in LBSNs

2017
The development of location-based social networks (LBSNs) generates large volume of check-in data. Point-of-interest recommendation (POI) is important for users to find some attractive venues, sometimes when users are in some places far away from their living cities.
Zhong Guo, Ma Changyi
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Detecting overlapping communities in LBSNs by fuzzy subtractive clustering

Social Network Analysis and Mining, 2018
With the increasing popularity of location-based social networks (LBSNs), community detection has emerged as an important and practical issue. One of the main shortcomings of the previous methods is that cluster’s centers have been selected randomly in clustering the communities; therefore, different results are obtained in each execution.
Mohammad Ghane'i-Ostad, Hamed Vahdat-Nejad, Majid Abdolrazzagh-Nezhad   +2 more
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A Friend Recommendation Algorithm Based on Multiple Factors in LBSNs

2015 12th Web Information System and Application Conference (WISA), 2015
In location-based social networks, the current friend recommendation algorithms just take a relatively single factor into account without comprehensive evaluations. To solve this problem, we design a framework - Multiple Heterogeneous Social Network (MHSN) according to users' profiles, check-in records and interests. Based on this framework, we propose
Tiancheng Zhang 0001, Wei Wang 0011, Dejun Yue, Ge Yu 0001   +3 more
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LocRec: Rule-Based Successive Location Recommendation in LBSN

2018 IEEE International Conference on Communications (ICC), 2018
Successive 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, Abderrahim Benslimane, Philippe Fournier-Viger, Nasreddine Lagraa   +3 more
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Using Visualization to Explore Original and Anonymized LBSN Data

Computer Graphics Forum, 2016
AbstractWe 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.
Ebrahim Tarameshloo, M. Hosseinkhani Loorak, Philip W. L. Fong, Sheelagh Carpendale   +3 more
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A Novel Social Search Model Based on Clustering Friends in LBSNs

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 2017
With the development of online social networks (OSNs), OSNs have become an indispensable part in people’s life. People tend to search information through OSNs rather than traditional search engines. Especially with the appearance of location-based social networks (LBSNs), social search in LBSNs is increasingly important in the burgeoning mobile trend ...
Jiuxin Cao, Cao Jiuxin
exaly   +2 more sources

Semantic analysis of spatial temporal trajectory in LBSNs [PDF]

Scientia Sinica Informationis, 2017
Spatial temporal data has associated multidimensional features. Deep learning has attracted much attention due to its ability to perform high-level abstraction of complex data. In this paper, we give the definition of the track-data based on its characteristics, and build a spatial temporal semantic trajectory model using Word2vec as its foundation. We
Haoteng YIN, Yang LIU
exaly   +2 more sources

Feature tendency based location prediction in LBSNs

2016 18th International Conference on Advanced Communication Technology (ICACT), 2016
The development of location-based social networks (LBSNs) has brought in massive users' mobility data, providing an unprecedented opportunity to study human mobile behavior. However, the existing location prediction methods suffer from incompleteness of mobility data and disability of selecting the effective feature.
Zi Xing, Hui Tian, Tu Chen, Jing Zhang
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Genetic Location-Based Social Networks (G-LBSN)

Proceedings of the 3rd International Workshop on Location and the Web, 2010
Despite much advances in both general and targeted Social Network Services (SNS) and Location-Based Social Networks (LBSN), there is currently a void in literatures on SNS that form temporary social networks to address specific problems and employ intelligent classification of members and coordination of tasks toward goal oriented action.
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