Personalised Recommendations for the BBC iPlayer: Initial approach and current challenges-Reference-Cited by-同舟云学术

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Personalised Recommendations for the BBC iPlayer: Initial approach and current challenges

Published:2023-09-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 17th ACM Conference on Recommender Systems
language:
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Author:

Clark Benjamin Richard¹^ORCID,Grivcova Kristine¹^ORCID,Proutskova Polina¹^ORCID,Walker Duncan Martin²^ORCID

Affiliation:

1. Research and Development, British Broadcasting Corporation, United Kingdom

2. British Broadcasting Corporation, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3604915.3608867

Reference21 articles.

1. Joeran Beel. 2017. It’s Time to Consider "Time" when Evaluating Recommender-System Algorithms [Proposal]. arxiv:1708.08447 [cs.IR] Joeran Beel. 2017. It’s Time to Consider "Time" when Evaluating Recommender-System Algorithms [Proposal]. arxiv:1708.08447 [cs.IR]

2. Building Public Service Recommenders: Logbook of a Journey

3. British Broadcasting Corporation . 2017. Data Science Research Partnership. Retrieved May 1, 2023 from https://www.bbc.co.uk/rd/projects/data-science-research-partnership British Broadcasting Corporation. 2017. Data Science Research Partnership. Retrieved May 1, 2023 from https://www.bbc.co.uk/rd/projects/data-science-research-partnership

4. Deep Neural Networks for YouTube Recommendations

5. Paolo Cremonesi and Dietmar Jannach . 2021. Progress in recommender systems research: Crisis? What crisis?AI Magazine 42, 3 ( 2021 ), 43–54. Paolo Cremonesi and Dietmar Jannach. 2021. Progress in recommender systems research: Crisis? What crisis?AI Magazine 42, 3 (2021), 43–54.

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