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A Framework for Evaluating Personalized Ranking Systems by Fusing Different Evaluation Measures

  • Published:2021-07 Issue: Volume:25 Page:100211
  • ISSN:2214-5796
  • Container-title:Big Data Research
  • language:en
  • Short-container-title:Big Data Research

Author:

Eftimov Tome,Paudel Bibek,Popovski GorjanORCID,Kocev DragiORCID

Funder

Javna Agencija za Raziskovalno Dejavnost RS

Publisher

Elsevier BV

Subject

Information Systems and Management,Computer Science Applications,Information Systems,Management Information Systems

Reference45 articles.

1. Everything is a recommendation;Mullaney;MIT Technol. Rev.,2015

2. Past, present, and future of recommender systems: an industry perspective;Amatriain,2016

3. Lessons from the netflix prize challenge;Bell;ACM SIGKDD Explor. Newsl.,2007

4. Recommender systems — beyond matrix completion;Jannach;Commun. ACM,2016

5. Offline and online evaluation of news recommender systems at swissinfo.ch;Garcin,2014

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1. Exploring the Landscape of Recommender Systems Evaluation: Practices and Perspectives;ACM Transactions on Recommender Systems;2023-10-28

2. Filter bubbles in recommender systems: Fact or fallacy—A systematic review;WIREs Data Mining and Knowledge Discovery;2023-08-03

3. Event Recommendation Based on Heterogeneous Social Network Information and Time Information;Proceedings of the 4th International Conference on Advanced Information Science and System;2022-11-25

4. Being Diverse is Not Enough: Rethinking Diversity Evaluation to Meet Challenges of News Recommender Systems;Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization;2022-07-04

5. Trust management and data protection for online social networks;IET Communications;2022-05-03
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