Classification, ranking, and top-K stability of recommendation algorithms
Gediminas Adomavicius (Department of Information and Decision Sciences, Carlson School of Management, University of Minnesota, Minneapolis, Minnesota), Jingjing Zhang (Department of Operations and Decision Technologies, Kelley School of Business, Indiana University, Bloomington, Indiana)
| Year of publication: |
2016
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|---|---|
| Authors: | Adomavicius, Gediminas ; Zhang, Jingjing |
| Published in: |
INFORMS journal on computing : JOC. - Catonsville, MD : INFORMS, ISSN 1091-9856, ZDB-ID 1316077-1. - Vol. 28.2016, 1, p. 129-147
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| Subject: | recommender systems | evaluation of recommender systems | classification stability | ranking stability | top-K stability | Personalisierung | Personalization | Ranking-Verfahren | Ranking method | Klassifikation | Classification | Algorithmus | Algorithm | Theorie | Theory | Bewertung | Evaluation |