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RED: a Rich Epinions Dataset for Recommender Systems

Abstract : Recommender Systems require speci c datasets to evaluate their approach. They do not require the same information: descriptions of users or items or users interactions may be necessary, which is not gathered in today datasets. In this paper, we provide a dataset containing reviews from users on items, trust values between users, items category, categories hierarchy and users expertise on categories. This dataset can be used to evaluate various Recommender Systems using Collaborative Filtering, Content-Based or Trust-Based.
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https://hal.archives-ouvertes.fr/hal-01010246
Contributor : Frédérique Laforest <>
Submitted on : Thursday, June 19, 2014 - 2:15:27 PM
Last modification on : Wednesday, November 20, 2019 - 3:18:54 AM
Document(s) archivé(s) le : Friday, September 19, 2014 - 11:07:09 AM

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Liris-5787RED.pdf
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  • HAL Id : hal-01010246, version 1

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Simon Meyffret, Emmanuel Guillot, Lionel Médini, Frédérique Laforest. RED: a Rich Epinions Dataset for Recommender Systems. [Research Report] LIRIS. 2012. ⟨hal-01010246⟩

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