A formal model for user preference

Author

Sung Young Jung ; Hong, Jeong-Hee ; Kim, Taek-Soo

Author_Institution

Machine Intelligence Group, LG Electron. Inst. of Technol., Seoul, South Korea

fYear

2002

fDate

2002

Firstpage

235

Lastpage

242

Abstract

Personalization and recommendation systems require a formalized model for user preference. We present the formal model of preference including positive preference and negative preference. For rare events, we apply the probability of random occurrence in order to reduce noise effects caused by data sparseness. Pareto distribution is adopted for the random occurrence probability. We also present the method for combining information of joint feature variables in different sizes by dynamic weighting using random occurrence probability.

Keywords

Pareto distribution; data mining; electronic commerce; information resources; user modelling; Pareto distribution; data mining; data sparseness; dynamic weighting; e-commerce; formal model; negative preference; noise effects; personalization; positive preference; random occurrence; random occurrence probability; rare events; recommendation systems; user preference model; Collaboration; Decision theory; History; Information filtering; Information filters; Lungs; Machine intelligence; Navigation; Noise reduction; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on

Print_ISBN

0-7695-1754-4

Type

conf

DOI

10.1109/ICDM.2002.1183908

Filename

1183908