The wisdom of the few: A collaborative filtering approach based on expert opinions from the web

Xavier Amatriain, Neal Lathia, Josep M. Pujol, Haewoon Kwak, Nuria Oliver

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

103 Citations (Scopus)

Abstract

Nearest-neighbor collaborative filtering provides a successful means of generating recommendations for web users. However, this approach suffers from several shortcomings, including data sparsity and noise, the cold-start problem, and scalability. In this work, we present a novel method for recommending items to users based on expert opinions. Our method is a variation of traditional collaborative filtering: rather than applying a nearest neighbor algorithm to the user-rating data, predictions are computed using a set of expert neighbors from an independent dataset, whose opinions are weighted according to their similarity to the user. This method promises to address some of the weaknesses in traditional collaborative filtering, while maintaining comparable accuracy. We validate our approach by predicting a subset of the Netflix data set. We use ratings crawled from a web portal of expert reviews, measuring results both in terms of prediction accuracy and recommendation list precision. Finally, we explore the ability of our method to generate useful recommendations, by reporting the results of a user-study where users prefer the recommendations generated by our approach.

Original languageEnglish
Title of host publicationProceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
Pages532-539
Number of pages8
DOIs
Publication statusPublished - 28 Dec 2009
Event32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009 - Boston, MA, United States
Duration: 19 Jul 200923 Jul 2009

Publication series

NameProceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009

Other

Other32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
CountryUnited States
CityBoston, MA
Period19/7/0923/7/09

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Keywords

  • Collaborative filtering
  • Cosine similarity
  • Experts
  • Nearest neighbors
  • Recommender system
  • Top-N recommendations

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

Cite this

Amatriain, X., Lathia, N., Pujol, J. M., Kwak, H., & Oliver, N. (2009). The wisdom of the few: A collaborative filtering approach based on expert opinions from the web. In Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009 (pp. 532-539). (Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009). https://doi.org/10.1145/1571941.1572033