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  Optimizing the Recency-Relevance-Diversity Trade-offs in Non-personalized News Recommendations

Chakraborty, A., Ghosh, S., Ganguly, N., & Gummadi, K. (2019). Optimizing the Recency-Relevance-Diversity Trade-offs in Non-personalized News Recommendations. Information Retrieval Journal, 22, 447-475. doi:10.1007/s10791-019-09351-2.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0005-F97E-6 Version Permalink: https://hdl.handle.net/21.11116/0000-000A-96D8-9
Genre: Journal Article
Other : Optimizing the Recency-Relevancy Trade-off in Online News Recommendations

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Chakraborty2019_Article_OptimizingTheRecency-relevance.pdf (Publisher version), 2MB
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Chakraborty2019_Article_OptimizingTheRecency-relevance.pdf
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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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 Creators:
Chakraborty, Abhijnan1, Author           
Ghosh, Saptarshi1, Author           
Ganguly, Niloy2, Author           
Gummadi, Krishna1, Author           
Affiliations:
1Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society, ou_2105291              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 20192019
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Chakraborty_Optimizing2019
DOI: 10.1007/s10791-019-09351-2
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Project name : FairSocialComputing
Grant ID : 789373
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Information Retrieval Journal
Source Genre: Journal
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Publ. Info: New York, NY : Springer
Pages: - Volume / Issue: 22 Sequence Number: - Start / End Page: 447 - 475 Identifier: -