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Recommender Systems Evaluation

  • Reference work entry
  • First Online:
Encyclopedia of Social Network Analysis and Mining

Synonyms

Evaluation; Methods; Metrics; Recommendation systems; Reproducibility

Glossary

AUC:

Area under the curve

CF:

Collaborative filtering

CTR:

Click-through rate

DCG:

Discounted cumulative gain

ILD:

Intra-list diversity

IR:

Information retrieval

MAE:

Mean absolute error

MAP:

Mean average precision

ML:

Machine learning

RMSE:

Root-mean-squared error

ROC:

Receiver operating characteristic

RS:

Recommender system

Definition

The evaluation of RSs has been, and still is, the object of active research in the field. Since the advent of the first RS, recommendation performance has been usually equated to the accuracy of rating prediction, that is, estimated ratings are compared against actual ratings, and differences between them are computed by means of the MAE and RMSE metrics. In terms of the effective utility of recommendations for users, there is, however, an increasing realization that the quality (precision) of a ranking of recommended items can be more important than the accuracy in...

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Authors and Affiliations

  1. Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049, Madrid, Spain

    Alejandro Bellogín

  2. School of Informatics, University of Skövde, Högskolevägen, Box 408, 541 28, Skövde, Sweden

    Alan Said

Authors
  1. Alejandro Bellogín
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Correspondence to Alejandro Bellogín .

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Editors and Affiliations

  1. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Reda Alhajj

  2. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Jon Rokne

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  1. Department of Computer Science, University of Bari "Aldo Moro", Bari, Italy

    Giovanni Semeraro

  2. Bari, Italy

    Cataldo Musto Ph.D

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Bellogín, A., Said, A. (2018). Recommender Systems Evaluation. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_110162

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