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IRS 2021 : IRS 2021: 2nd International Workshop on Industrial Recommendation Systems (conjunction with KDD 2021)

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Link: https://irsworkshop.github.io/2021/index.html
 
When Aug 14, 2021 - Aug 16, 2021
Where Singapore
Submission Deadline May 30, 2021
Notification Due Jun 20, 2021
Final Version Due Jul 10, 2021
Categories    recommender systems   machine learning   data mining
 

Call For Papers

Call for papers
2nd International Workshop on Industrial Recommendation Systems
To be held in conjunction with KDD 2021
August 14, 2021, Singapore
https://irsworkshop.github.io/2021/index.html

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Key Dates

Workshop paper and poster submissions: May 30, 2021
Workshop paper and poster notifications: June 20, 2021
Workshop papers for Camera-ready: July 10, 2021:

Workshop date: August 14 - 16, 2021
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Description

Recommendation systems are used widely across many industries, such as eCommerce, multimedia content platforms and social networks, to provide suggestions that a user will most likely consume or connect; thus, improving the user experience. This motivates people in both industry and research organizations to focus on personalization or recommendation algorithms, which has resulted in a plethora of research papers. While academic research mostly focuses on the performance of recommendation algorithms in terms of ranking quality or accuracy, it often neglects key factors that impact how a recommendation system will perform in a real-world environment. These key factors include but are not limited to: business metric definition and evaluation, recommendation quality control, data and model scalability, model interpretability, model robustness and fairness, and resource limitations, such as computing and memory resources budgets, engineering workforce cost, etc. The gap in constraints and requirements between academic research and industry limits the broad applicability of many of academia’s contributions for industrial recommendation systems. This workshop aspires to bridge this gap by bringing together researchers from both academia and industry. Its goal is to serve as a venue through which academic researchers become aware of the additional factors that may affect the adoption of an algorithm into real production systems, and how well it will perform if deployed. Industrial researchers will also benefit from sharing the practical insights, approaches, and frameworks as well.

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Along with SIGKDD 2021, IRS is officially going virtual.

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Topics

This workshop welcomes submissions from researchers and industrial practitioners broadly related to recommendation systems, such as novel recommendation models, efficient recommendation algorithms, novel industrial frameworks, etc. In order to emphasize the gap between the two communities, we extremely welcome submissions on industrial recommendation system infrastructures based on given resources, models and algorithms supported by the specific infrastructures, and frameworks or end-to-end systems that have been deployed in real world production.


Specific topics of interest are including but not limited to:

(1) Frameworks or end-to-end systems from industry are extremely welcomed.
(2) Scalable Recommender systems.
(3) Personalization, including personalized product recommendation, streaming content recommendation, ads recommendation, news and article recommendation, etc.
(4) New applications related to recommendation systems.
(5) Existing or novel infrastructures for recommendation systems.
(6) Interactive recommendation system with user feedback loop
(7) Explainability of recommendations.
(8) Fairness, privacy and security in recommender systems.
(9) Recommendations under multi-objective and constraints.
(10) Reproducibility of models and evaluation metrics.
(11) Unbiased recommendation.
(12) User research studies on real-world recommender systems.
(13) Business impact of recommendation systems.


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Submission Directions

The workshop accepts long papers (limited to 9 pages), short papers (6 pages), posters (4 pages), abstracts and demos (2 pages). Paper submission and reviewing will be following the directions of the KDD main conference. Reviews are not double-blind, and author names and affiliations should be listed. Submissions should include all content and references within the limited pages, and must be in PDF format and formatted according to the new Standard ACM Conference Proceedings Template. For LaTeX users: unzip acmart.zip, make, and use sample-sigconf.tex as a template. Additional information about formatting and style files is available online at: https://www.acm.org/publications/proceedings-template. Papers that do not meet the formatting requirements will be rejected without review. In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility.

For details of submission, please check the website of the workshop: https://irsworkshop.github.io/2021/

Please submit your paper through this Easychair link. Please reach out to irs-kdd@googlegroups.com or irs2021-0@easychair.org for any questions.

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