LEARNING NEIGHBOURHOOD-BASED COLLABORATIVE FILTERING PARAMETERS

J. Griffith, C. O'Riordan, H. Sorensen

Abstract

The work outlined in this paper uses a genetic algorithm to learn the optimal set of parameters for a neighbourhood-based collaborative filtering approach. The motivation is firstly to re-assess whether the default parameter values often used are valid and secondly to assess whether different datasets require different parameter settings. Three datasets are considered in this initial investigation into the approach: Movielens, Bookcrossing and Lastfm.

References

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Paper Citation


in Harvard Style

Griffith J., O'Riordan C. and Sorensen H. (2011). LEARNING NEIGHBOURHOOD-BASED COLLABORATIVE FILTERING PARAMETERS . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011) ISBN 978-989-8425-79-9, pages 444-447. DOI: 10.5220/0003657404520455


in Bibtex Style

@conference{kdir11,
author={J. Griffith and C. O'Riordan and H. Sorensen},
title={LEARNING NEIGHBOURHOOD-BASED COLLABORATIVE FILTERING PARAMETERS},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)},
year={2011},
pages={444-447},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003657404520455},
isbn={978-989-8425-79-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)
TI - LEARNING NEIGHBOURHOOD-BASED COLLABORATIVE FILTERING PARAMETERS
SN - 978-989-8425-79-9
AU - Griffith J.
AU - O'Riordan C.
AU - Sorensen H.
PY - 2011
SP - 444
EP - 447
DO - 10.5220/0003657404520455