Webpage Recommendation Model in Personalized Service based on the Group Clustering

DOI

10.2991/ameii-15.2015.39How to use a DOI?

Keywords

Group Clustering; Webpage Recommendation; Personalized Service

Abstract

This paper proposes an effective model to realize the Webpage recommendation in personalized service based on the data mining technology. Applying user interest feature vector and user session feature vector to represents user’s interest and generate user groups’ interests by clustering, and extends the individual user interest. The experiment proves that the model is effective and accuracy.

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  - Rong Fu
AU  - Yi He
AU  - Yingqian Zhang
PY  - 2015/04
DA  - 2015/04
TI  - Webpage Recommendation Model in Personalized Service based on the Group Clustering
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 213
EP  - 218
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.39
DO  - 10.2991/ameii-15.2015.39
ID  - Fu2015/04
ER  -