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A user customized service provider framework based on machine learning
- Title
- A user customized service provider framework based on machine learning
- Authors
- Kim; S.; Hong; E.; Park; B.; H.
- Ewha Authors
- 박형곤
- SCOPUS Author ID
- 박형곤
- Issue Date
- 2015
- Journal Title
- International Conference on Ubiquitous and Future Networks, ICUFN
- ISSN
- 2165-8528
- Citation
- International Conference on Ubiquitous and Future Networks, ICUFN vol. 2015-August, pp. 23 - 25
- Keywords
- K-fold cross-validation; location based service; Machine learning; support vector machine
- Publisher
- IEEE Computer Society
- Indexed
- SCOPUS
- Document Type
- Conference Paper
- Abstract
- In this paper, we propose a user customized service provider framework based on machine learning. The framework consists of mobile stations, data collector, analysis tools and service applications. As an analysis tool, we deploy machine learning techniques, in particular, support vector machine which generates learning model and precise classifiers. Moreover, K-fold cross-validation is used to achieve better accurate inference from the collected data. Then, we develop a predictor that predicts users' behavior patterns from the information of time connections and APs. This enables to provide adaptive services customized for end-users, e.g., smart phone push notifications services. © 2015 IEEE.
- DOI
- 10.1109/ICUFN.2015.7182488
- ISBN
- 9781479989935
- Appears in Collections:
- 공과대학 > 전자전기공학전공 > Journal papers
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