Study on Multi-criteria Personalized Recommendation Algorithm

DOI

10.2991/iccasm.2012.33How to use a DOI?

Keywords

E-commerce, Personalized Recommendation, Multi-criteria Algorithm, Aggregate Function

Abstract

Personalized recommendation plays an important role in E-commerce. Single-criteria recommendation algorithm has the features of simplicity and high efficiency but also can easily have the problems of cold startup and sparse data. Multi-criteria recommendation algorithm is to carry out prediction from two prospects: customer and commodity, and fully evaluate and give rates to customer similarity, customer’s evaluation for commodity, rank of commodity sales, and commodity similarity, etc. The commodities in a same layer are given an aggregated rate respectively by borrowing the concept of commodity hierarchical tree from aggregation. Eventually the advantages of multi-criteria recommendation algorithm are summarized.

Copyright

© 2012, 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  - Ya Luo
AU  - Li Zhao
PY  - 2012/08
DA  - 2012/08
TI  - Study on Multi-criteria Personalized Recommendation Algorithm
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 129
EP  - 131
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.33
DO  - 10.2991/iccasm.2012.33
ID  - Luo2012/08
ER  -