A Collaborative Filtering Algorithm Based on Double Clustering and User Trust

DOI

10.2991/icsnce-16.2016.8How to use a DOI?

Keywords

Collaborative filtering algorithm; Double clustering; User trust; Score prediction; Recommender system

Abstract

A collaborative filtering algorithm based on double clustering and user trust to solve data sparse and cold start problem is present. This algorithm uses user-clustering matrix to measure the user's degree of similarity, which could reduce the dimension of the user-item matrix. On the other hand it uses user level trust to perform predictions in rating predicting step. The experiments results show that this method could relieve the sparsity problem and improve the accuracy of the prediction results.

Copyright

© 2016, 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  - Tonglong Tang
AU  - Xiaoyu Li
PY  - 2016/07
DA  - 2016/07
TI  - A Collaborative Filtering Algorithm Based on Double Clustering and User Trust
BT  - Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
PB  - Atlantis Press
SP  - 31
EP  - 37
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsnce-16.2016.8
DO  - 10.2991/icsnce-16.2016.8
ID  - Tang2016/07
ER  -