Zobrazeno 1 - 10
of 114
pro vyhledávání: '"mobile data mining"'
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-28 (2019)
Abstract Due to the increasing popularity of recent advanced features and context-awareness in smart mobile phones, the contextual data relevant to users’ diverse activities with their phones are recorded through the device logs. Modeling and predi
Externí odkaz:
https://doaj.org/article/2bf408c4f28f4416a8e48b72f0b7b7bd
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-21 (2019)
Abstract Due to the advanced features in recent smartphones and context-awareness in mobile technologies, users’ diverse behavioral activities with their phones and associated contexts are recorded through the device logs. Behavioral patterns of sm
Externí odkaz:
https://doaj.org/article/f11a4b07085249bea3116630743ffe40
Publikováno v:
Frontiers in Public Health, Vol 8 (2021)
Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users,
Externí odkaz:
https://doaj.org/article/03be3e73879f4813ad62ba05e8ae508f
Autor:
Iqbal Sarker
Publikováno v:
EAI Endorsed Transactions on Scalable Information Systems, Vol 6, Iss 20 (2019)
Context-awareness in phone call prediction can help us to build many intelligent applications to assist the end mobile phone users in their daily life. Social context, particularly, the interpersonal relationship between individuals, is one of the ke
Externí odkaz:
https://doaj.org/article/eaa61df22eb14ba28ea93ffcd40aab72
Autor:
Iqbal H. Sarker
Publikováno v:
EAI Endorsed Transactions on Scalable Information Systems, Vol 5, Iss 19 (2018)
Due to the popularity of smart mobile phones and context-aware technology, various contextual data relevant to users’ diverse activities with mobile phones is available around us. This enables the study on mobile phone data and context-awareness in
Externí odkaz:
https://doaj.org/article/c9ff554ff61d457491339a46e16f6f02
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-21 (2019)
Due to the advanced features in recent smartphones and context-awareness in mobile technologies, users’ diverse behavioral activities with their phones and associated contexts are recorded through the device logs. Behavioral patterns of smartphone
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f7dc373fabf79ee2c5974bb66a367ab
http://link.springer.com/article/10.1186/s40537-019-0211-6
http://link.springer.com/article/10.1186/s40537-019-0211-6
Autor:
Wang, S., Scheider, S., Sporrel, K., Deutekom, Marije, Timmer, Joris, Kröse, Ben J.A., Sub Intelligent Systems, Urban Accessibility and Social Inclusion
Publikováno v:
Frontiers in Public Health, 8, 1. Frontiers Media S.A.
Frontiers in Public Health, Vol 8 (2021)
Frontiers in Public Health
Frontiers in Public Health, Vol 8 (2021)
Frontiers in Public Health
Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84e433f87a9c0bd63aa6c9baade7f7b0
https://dspace.library.uu.nl/handle/1874/409950
https://dspace.library.uu.nl/handle/1874/409950
Akademický článek
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Autor:
Mustapha Akinkunmi
Publikováno v:
Synthesis Lectures on Engineering. 12:1-181
This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of market intelligence, this book is designed to ins
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b80d4ad953c5272080504d2aba6bf03
https://doi.org/10.2200/s00838ed1v01y201803eng030
https://doi.org/10.2200/s00838ed1v01y201803eng030
Publikováno v:
The Computer Journal. 61:349-368
Mobile phones can record individual's daily behavioral data as a time-series. In this paper, we present an effective time-series segmentation technique that extracts optimal time segments of individual's similar behavioral characteristics utilizing t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f73a0fea19bb22c8aecc5501426f82c8
https://doi.org/10.1093/comjnl/bxx082
https://doi.org/10.1093/comjnl/bxx082