A Method to Solve Cold-Start Problem in Recommendation System based on Social Network Sub-community and Ontology Decision Model

DOI

10.2991/icmt-13.2013.20How to use a DOI?

Keywords

Cold-start, recommendation system, ontology model, decision tree, collaborative filtering, social sub-community

Abstract

The paper presents a method to solve Cold-start problem in collaborative filtering recommendation system. Social sub-community is divided following analyzing exiting users’ history data and mining relationship between each other. Then ontology decision model is built in the basis of sub-community and users’ static information, which makes recommendation for new user based on his static ontology information. At last, the proposed method is used to recommenditems tonew users. In this paper, data simulation experiment is taken to test the technical method.

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  - Chen Meng
AU  - Yang Cheng
AU  - Chen Jiechao
AU  - Yi Peng
PY  - 2013/11
DA  - 2013/11
TI  - A Method to Solve Cold-Start Problem in Recommendation System based on Social Network Sub-community and Ontology Decision Model
BT  - Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SP  - 159
EP  - 166
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.20
DO  - 10.2991/icmt-13.2013.20
ID  - Meng2013/11
ER  -