A Micro blog Recommendation System Based on User Clustering

DOI

10.2991/iccset-14.2015.91How to use a DOI?

Keywords

micro blog, recommendation system, cluster, semantic dictionary, similarity

Abstract

Nowadays, micro blog has been widely used as a platform of information sharing. How to help users to find what they are interested in from massive amount of data becomes a very challenging issue. Some micro blog recommend systems are user-based and its effect is not significant. In this paper, we implement the recommendation system based on micro blog, users can subscribe the post which they are interested in, and system will recommend the related posts to users combined with user interest. This paper cluster users by their interest and experimental results show that the improved K-Means clustering algorithm can achieve a better accuracy and running time and our algorithm is more effective than traditional algorithm.

Copyright

© 2015, 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  - Lei Chen
AU  - Chao Jiang
AU  - Wei Wang
PY  - 2015/01
DA  - 2015/01
TI  - A Micro blog Recommendation System Based on User Clustering
BT  - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 408
EP  - 411
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccset-14.2015.91
DO  - 10.2991/iccset-14.2015.91
ID  - Chen2015/01
ER  -