A Study of Evaluation Metrics for Recommender Algorithms

Jennifer Redpath, CM Shapcott, SI McClean, Liming Chen

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

Abstract

There are inherent problems with evaluating the accuracy of recommender systems. Commonly-used metrics for recommender systems depend on the number of recommendations produced and the number of hidden items withheld, making it difficult to directly compare one system with another. In this paper we compare recommender algorithms using two datasets; the standard MovieLens set and an e-commerce dataset that has implicit ratings based on browsing behaviour. We introduce a measure that aids in the comparison and show how to compare results with baseline predictions based on random recommendation selections.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages10
Publication statusPublished - 25 Aug 2008
EventThe 19th Irish Conference on Artificial Intelligence and Cognitive Science -
Duration: 25 Aug 2008 → …

Conference

ConferenceThe 19th Irish Conference on Artificial Intelligence and Cognitive Science
Period25/08/08 → …

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Recommender systems

Cite this

Redpath, J., Shapcott, CM., McClean, SI., & Chen, L. (2008). A Study of Evaluation Metrics for Recommender Algorithms. In Unknown Host Publication
Redpath, Jennifer ; Shapcott, CM ; McClean, SI ; Chen, Liming. / A Study of Evaluation Metrics for Recommender Algorithms. Unknown Host Publication. 2008.
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title = "A Study of Evaluation Metrics for Recommender Algorithms",
abstract = "There are inherent problems with evaluating the accuracy of recommender systems. Commonly-used metrics for recommender systems depend on the number of recommendations produced and the number of hidden items withheld, making it difficult to directly compare one system with another. In this paper we compare recommender algorithms using two datasets; the standard MovieLens set and an e-commerce dataset that has implicit ratings based on browsing behaviour. We introduce a measure that aids in the comparison and show how to compare results with baseline predictions based on random recommendation selections.",
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Redpath, J, Shapcott, CM, McClean, SI & Chen, L 2008, A Study of Evaluation Metrics for Recommender Algorithms. in Unknown Host Publication. The 19th Irish Conference on Artificial Intelligence and Cognitive Science, 25/08/08.

A Study of Evaluation Metrics for Recommender Algorithms. / Redpath, Jennifer; Shapcott, CM; McClean, SI; Chen, Liming.

Unknown Host Publication. 2008.

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

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T1 - A Study of Evaluation Metrics for Recommender Algorithms

AU - Redpath, Jennifer

AU - Shapcott, CM

AU - McClean, SI

AU - Chen, Liming

PY - 2008/8/25

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N2 - There are inherent problems with evaluating the accuracy of recommender systems. Commonly-used metrics for recommender systems depend on the number of recommendations produced and the number of hidden items withheld, making it difficult to directly compare one system with another. In this paper we compare recommender algorithms using two datasets; the standard MovieLens set and an e-commerce dataset that has implicit ratings based on browsing behaviour. We introduce a measure that aids in the comparison and show how to compare results with baseline predictions based on random recommendation selections.

AB - There are inherent problems with evaluating the accuracy of recommender systems. Commonly-used metrics for recommender systems depend on the number of recommendations produced and the number of hidden items withheld, making it difficult to directly compare one system with another. In this paper we compare recommender algorithms using two datasets; the standard MovieLens set and an e-commerce dataset that has implicit ratings based on browsing behaviour. We introduce a measure that aids in the comparison and show how to compare results with baseline predictions based on random recommendation selections.

M3 - Conference contribution

BT - Unknown Host Publication

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Redpath J, Shapcott CM, McClean SI, Chen L. A Study of Evaluation Metrics for Recommender Algorithms. In Unknown Host Publication. 2008