Personalization Recommendation Framework in Mobile Computing

DOI

10.2991/icacie-17.2017.10How to use a DOI?

Keywords

Recommendation, Mobile, Personalization, LBS

Abstract

Recently, with the development of IT technology, the transition to the ubiquitous environment has been made so that various devices can be used to access information anytime and anywhere, and the computer can decide to provide useful services to the user. In this context aware mobile environment, context aware information is collected by sensors around the user and used to infer the user's current situation with personal information such as user profile. The inferred context information is used to provide a suitable service for the user. Recommendation techniques such as case based reasoning and collaborative filtering have also been studied in mobile computing, the web, and other fields. These technologies provide services by using personal profiles and user preference ratings. However, previous techniques used in ubiquitous computing did not take into account the privacy concerns and the accuracy of the contextual Therefore, access rights management is very important to adapt to information resources that requires the system. In this paper, we assume a context-aware model based on a profile of user information that provides efficient control rights to users through active classification, inference and resources. Therefore, a situation adaptive service recommendation technique is proposed in which location, time, and frequency information of frequently used services are stored, and services expected to be used at any location are stored in a storage device.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wonseok Kim
AU  - Euiin Choi
PY  - 2017/08
DA  - 2017/08
TI  - Personalization Recommendation Framework in Mobile Computing
BT  - Proceedings of the 2017 2nd International Conference on Automatic Control and Information Engineering (ICACIE 2017)
PB  - Atlantis Press
SP  - 45
EP  - 48
SN  - 2352-5401
UR  - https://doi.org/10.2991/icacie-17.2017.10
DO  - 10.2991/icacie-17.2017.10
ID  - Kim2017/08
ER  -