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Item-based relevance modelling of recommendations for getting rid of long tail products

  • Published:2016-07 Issue: Volume:103 Page:41-51
  • ISSN:0950-7051
  • Container-title:Knowledge-Based Systems
  • language:en
  • Short-container-title:Knowledge-Based Systems

Author:

Valcarce DanielORCID,Parapar Javier,Barreiro Álvaro

Funder

Ministerio de Educación, Cultura y Deporte

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference41 articles.

1. Improving aggregate recommendation diversity using ranking-based techniques;Adomavicius;IEEE Trans. Knowl. Data Eng.,2012

2. The Long Tail: Why the Future of Business Is Selling Less of More;Anderson,2008

3. Movie recommender system for profit maximization;Azaria,2013

4. A comparative analysis of offline and online evaluations and discussion of research paper recommender system evaluation.;Beel,2013

5. Precision-oriented evaluation of recommender systems;Bellogín,2011

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1. Predicting user demographics based on interest analysis in movie dataset;Multimedia Tools and Applications;2024-02-03

2. Design and implementation of college entrance examination volunteer intelligent filling system based on big data;International Conference on Computer Network Security and Software Engineering (CNSSE 2022);2022-10-03

3. A Survey of Long-Tail Item Recommendation Methods;Wireless Communications and Mobile Computing;2021-11-29

4. An approach to user knowledge acquisition in product design;Advanced Engineering Informatics;2021-10

5. Enhancing long tail item recommendation in collaborative filtering: An econophysics-inspired approach;Electronic Commerce Research and Applications;2021-09
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