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Soft Computing

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08.05.2017 | Focus

An efficient approach to understanding social evolution of location-focused online communities in location-based services

verfasst von: Fei Hao, Doo-Soon Park, Dae-Soo Sim, Min Jeong Kim, Young-Sik Jeong, Jong-Hyuk Park, Hyung-Seok Seo

Erschienen in: Soft Computing | Ausgabe 13/2018

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Abstract

The booming and novel emerging promising technologies on ubiquitous computing, GPS positioning, are facilitating the development of location-based services (LBSs). Particularly, understanding the dynamic topological structures of mobile users in LBSs who visit the same physical locations has many meaningful applications including friend recommendation, location-sensitive items recommendation, and privacy management. In this paper, we proposed a novel m-triadic concept-based approach for uncovering the social evolution of location-focused online communities in LBSs. Firstly, an m-triadic concept-based location-focused online communities detection approach is presented. Further, the social evolution of the community is characterized by the time series triadic concepts in which the objectives contain the targeted users.

Vorheriger Artikel Advances in intelligence and internet of things for human-centric computing

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Titel: An efficient approach to understanding social evolution of location-focused online communities in location-based services
verfasst von: Fei Hao
Doo-Soon Park
Dae-Soo Sim
Min Jeong Kim
Young-Sik Jeong
Jong-Hyuk Park
Hyung-Seok Seo
Publikationsdatum: 08.05.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 13/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-017-2627-2

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