Collaborative filtering using random neighbours in peer-to-peer networks

Arno Bakker*, Elth Ogston, Maarten van Steen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

16 Citations (Scopus)

Abstract

Traditionally, collaborative filtering (CF) algorithms used for recommendation operate on complete knowledge. This makes these algorithms hard to employ in a decentralized context where not all users' ratings can be available at all locations. In this paper we investigate how the well-known neighbourhood-based CF algorithm by Herlocker et al. operates on partial knowledge; that is, how many similar users does the algorithm actually need to produce good recommendations for a given user, and how similar must those users be. We show for the popular MovieLens 1,000,000 and Jester datasets that sufficiently good recommendations can be made based on the ratings of a neighbourhood consisting of a relatively small number of randomly selected users.

Original languageEnglish
Title of host publicationCNIKM '09
Subtitle of host publicationProceedings of the 1st ACM International Workshop on Complex Networks in Information and Knowledge Management (CNIKM 2009)
Place of PublicationNew York, NY
PublisherACM Publishing
Pages67-74
Number of pages8
ISBN (Print)978-1-60558-807-0
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event1st ACM International Workshop on Complex Networks in Information and Knowledge Management, , CNIKM'09 - Hong Kong, China
Duration: 6 Nov 20096 Nov 2009

Conference

Conference1st ACM International Workshop on Complex Networks in Information and Knowledge Management, , CNIKM'09
CountryChina
CityHong Kong
Period6/11/096/11/09
OtherCo-located with the 18th ACM International Conference on Information and Knowledge Management, CIKM 2009

Keywords

  • Collaborative filtering
  • Metrics
  • Peer-to-peer networking
  • Recommender systems

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  • Cite this

    Bakker, A., Ogston, E., & van Steen, M. (2009). Collaborative filtering using random neighbours in peer-to-peer networks. In CNIKM '09 : Proceedings of the 1st ACM International Workshop on Complex Networks in Information and Knowledge Management (CNIKM 2009) (pp. 67-74). New York, NY: ACM Publishing. https://doi.org/10.1145/1651274.1651288