An efficient approach to understanding social evolution of location-focused online communities in location-based services
- Authors
- Hao, Fei; Park, Doo-Soon; Sim, Dae-Soo; Kim, Min Jeong; Jeong, Young-Sik; Park, Jong-Hyuk; Seo, Hyung-Seok
- Issue Date
- Jul-2018
- Publisher
- Springer Verlag
- Keywords
- LBSs; Location-focused online communities; M-triadic concepts; Time series triadic concepts; Social evolution
- Citation
- Soft Computing, v.22, no.13, pp 4169 - 4174
- Pages
- 6
- Journal Title
- Soft Computing
- Volume
- 22
- Number
- 13
- Start Page
- 4169
- End Page
- 4174
- URI
- https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/5860
- DOI
- 10.1007/s00500-017-2627-2
- ISSN
- 1432-7643
1433-7479
- 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.
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- Appears in
Collections - College of Engineering > Department of Computer Software Engineering > 1. Journal Articles

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