A hybrid approach for improving predictive accuracy of collaborative filtering algorithms

@article{Lekakos2006AHA,
  title={A hybrid approach for improving predictive accuracy of collaborative filtering algorithms},
  author={George Lekakos and George M. Giaglis},
  journal={User Modeling and User-Adapted Interaction},
  year={2006},
  volume={17},
  pages={5-40}
}
Recommender systems represent a class of personalized systems that aim at predicting a user’s interest on information items available in the application domain, operating upon user-driven ratings on items and/or item features. One of the most widely used recommendation methods is collaborative filtering that exploits the assumption that users who have agreed in the past in their ratings on observed items will eventually agree in the future. Despite the success of recommendation methods and… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 70 references

Consumer Behavior: Building Marketing Strategy

  • I. Hawkins, R. J. Best, K. A. Coney
  • Irwin/McGraw-Hill New York
  • 1998
Highly Influential
5 Excerpts

Consumer Profiles: An Introduction to Psychographics

  • B. Gunter, A. Furnham
  • 1992
Highly Influential
4 Excerpts

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