mRHR: A Modified Reciprocal Hit Rank Metric for Ranking Evaluation of Multiple Preferences in Top-N Recommender Systems

Date

2016-09-10

Author

Peker, Serhat
Koçyiğit, Altan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Average reciprocal hit rank (ARHR) is a commonly used metric for ranking evaluation of top-n recommender systems. However, it suffers from an important shortcoming that it cannot be applied when the user has multiple preferences at a time. In order to overcome this problem, a modified version of ARHR metric is introduced and applied to grocery shopping domain by conducting a series of experiments on real-life data. The results show that the proposed measure is feasible for ranking evaluation of Top-N recommender systems in the cases where the users have multiple preferences at a time or a specific time interval.

Subject Keywords

Top-N recommender systems , Ranking evaluation, ARHR , Reciprocal rank , Hit rank

URI

https://hdl.handle.net/11511/30829

DOI

https://doi.org/10.1007/978-3-319-44748-3_31

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

S. Peker and A. Koçyiğit, “mRHR: A Modified Reciprocal Hit Rank Metric for Ranking Evaluation of Multiple Preferences in Top-N Recommender Systems,” 2016, vol. 9883, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/30829.