Context-Aware Strategies For Recommender System On A Professional SNS Platform

DOI

10.2991/iccsee.2013.189How to use a DOI?

Keywords

recommender system, social network, collaborative filtering, collective intelligence, professional SNS platform

Abstract

The importance of recommender system on Social Network Services (SNS) platform has been recognized by researchers and practitioners in many disciplines, including e-commerce, information retrieval, social computing, data mining, marketing, etc. While a substantial amount of approaches focus on recommending the most relevant items to users on mainstream SNS platforms, there is still a lack of closer investigation into the context-aware strategies on professional SNS platform whose contextual information varies significantly from generic SNS platforms. Drawing upon existing algorithmic paradigms –content-based methods and collaborative filtering, this paper proposes context-aware strategies that cope with the need to recommend both users and items on a professional SNS platform. A case study has been demonstrated based on such approach and directions for future research have been discussed.

Copyright

© 2013, 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  - Xianghui Zhao
AU  - Hui Liu
AU  - Wen Tian
AU  - Zhaopei Zeng
AU  - Lin Ye
PY  - 2013/03
DA  - 2013/03
TI  - Context-Aware Strategies For Recommender System On A Professional SNS Platform
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 745
EP  - 748
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.189
DO  - 10.2991/iccsee.2013.189
ID  - Zhao2013/03
ER  -