An effective threshold-based neighbor selection in collaborative filtering

Tack Hun Kim, Sung Bong Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

In this paper we present a recommender system using an effective threshold-based neighbor selection in collaborative filtering. The proposed method uses the substitute neighbors of the test customer who may have an unusual preferences or who are the first rater. The experimental results show that the recommender systems using the proposed method find the proper neighbors and give a good prediction quality.

Original languageEnglish
Title of host publicationAdvances in Information Retrieval - 29th European Conference on IR Research, ECIR 2007, Proceedings
PublisherSpringer Verlag
Pages712-715
Number of pages4
ISBN (Print)3540714944, 9783540714941
DOIs
Publication statusPublished - 2007 Jan 1
Event29th European Conference on IR Research, ECIR 2007 - Rome, Italy
Duration: 2007 Apr 22007 Apr 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4425 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other29th European Conference on IR Research, ECIR 2007
CountryItaly
CityRome
Period07/4/207/4/5

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kim, T. H., & Yang, S. B. (2007). An effective threshold-based neighbor selection in collaborative filtering. In Advances in Information Retrieval - 29th European Conference on IR Research, ECIR 2007, Proceedings (pp. 712-715). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4425 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-71496-5_75