A Novel Personalized Recommendation Method in E-business Based on Kansei Image

DOI

10.2991/amcce-15.2015.285How to use a DOI?

Keywords

fuzzy theory; e-commerce; personalized recommendation; kansei image

Abstract

Personalized recommendation technique is an important technology to solve information overloaded in e-commerce. But recently new commodities are emerging constantly, so it is required to recommend commodities that consumers aren’t familiar with but interested in. Consequently our study proposes a method to mine consumer’s preference from the respective of consumer psychology. Consumers’ affective needs can be described in the form of kansei image preference and kansei image weight. Then recommendation results are produced to meet consumer’s quantitative affective needs. Finally by real historical data of 15 consumers online and surveys in the example of garments, validity of the method is verified.

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  - Guangqian Zhang
AU  - Enshui Yu
PY  - 2015/04
DA  - 2015/04
TI  - A Novel Personalized Recommendation Method in E-business Based on Kansei Image
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.285
DO  - 10.2991/amcce-15.2015.285
ID  - Zhang2015/04
ER  -