Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

Framework for Social Relationship Recommendation

Authors
Jia Chen, Tongge Xu, Zhang Xiong
Corresponding Author
Jia Chen
Available Online June 2017.
DOI
https://doi.org/10.2991/caai-17.2017.111How to use a DOI?
Keywords
big data; framework; recommendation; social relationships
Abstract
Find out the potential favorite data is the essence of recommendation techniques, which facilitates the recommendation techniques become a vital issue in the big data researches and applications. The traditional recommendation research and application centers on the commercial items and resources. We apply the recommendation to social relationships in social networks. We design a framework which can analyze and recommend various types of relationships. The framework has four modules and three work modes. Furthermore, we design a hybrid recommendation approach in the framework for the balancing between accuracy and efficiency. The framework can recommend the social relationships with high accuracy and low cost.
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Proceedings
2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/caai-17.2017.111How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jia Chen
AU  - Tongge Xu
AU  - Zhang Xiong
PY  - 2017/06
DA  - 2017/06
TI  - Framework for Social Relationship Recommendation
BT  - 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 494
EP  - 498
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.111
DO  - https://doi.org/10.2991/caai-17.2017.111
ID  - Chen2017/06
ER  -