A weighted sifting method to improve the effectiveness of collaborative filtering

Tuguldur Sumiya, Heungsun Park, Jonghoon Chun, Zoonky Lee, Sang Goo Lee, Eugene Kim, Donghoon Shin, Won Gyu Lee, Jinwook Choi, Juno Chang

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

In this paper, we improve the accuracy of the conventional collaborative filtering algorithm by proposing a weighted sifting method. The weighted sifting method preprocesses the given customer data to generate an adjusted customer data which we believe contains less noise than the original one, and thus effectively discriminates the preference weights of items for each customer. We present two alternative calculation methods for weight adjustment, and our experimental evaluation shows that both calculation methods result in better accuracy than traditional collaborative filtering.

Original languageEnglish
PagesB266-B269
Publication statusPublished - 2004
EventIEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering - Chiang Mai, Thailand
Duration: 2004 Nov 212004 Nov 24

Other

OtherIEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering
CountryThailand
CityChiang Mai
Period04/11/2104/11/24

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Sumiya, T., Park, H., Chun, J., Lee, Z., Lee, S. G., Kim, E., Shin, D., Lee, W. G., Choi, J., & Chang, J. (2004). A weighted sifting method to improve the effectiveness of collaborative filtering. B266-B269. Paper presented at IEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering, Chiang Mai, Thailand.