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KDD_OARS 2023 : 3rd workshop of Online and Adaptive Recommender Systems (OARS)at KDD 2023

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Link: https://oars-workshop.github.io/
 
When Aug 6, 2023 - Aug 10, 2023
Where Long Beach, CA
Submission Deadline Jun 9, 2023
Notification Due Jun 23, 2023
Final Version Due Jul 10, 2023
Categories    recsys   AI   machine learning   data science
 

Call For Papers

KDD 2023 Workshop on Online and Adaptive Recommender Systems (OARS)

Call For Papers
==================

KDD OARS is a half day workshop taking place on August 7th, 2023 in conjunction with KDD 2023 in Long Beach, CA, USA.

Workshop website: https://oars-workshop.github.io/
Important Dates:
==================
- Submissions Due - June 9th, 2023
- Notification - June 23rd, 2023
- Camera Ready Version of Papers Due - July 10th, 2023
- KDD OARS Workshop - August 7th, 2023

Details:
==================
The KDD workshop on online and adaptive recommender (OARS) will serve as a platform for publication and discussion of OARS. This workshop will bring together practitioners and researchers from academia and industry to discuss the challenges and approaches to implement OARS algorithms and systems, and improve user experiences by better modeling and responding to users’ intent.

We invite submission of papers and posters of two to ten pages (including references), representing original research, preliminary research results, proposals for new work, and position and opinion papers. All submitted papers and posters will be single-blind and will be peer reviewed by an international program committee of researchers of high repute. Accepted submissions will be presented at the workshop.

Topics of interest include, but are not limited to:
====================================
Novel algorithms and paradigms (deep learning, reinforcement learning, online learning etc.)
Use cases (product, content, fashion/decor, job, healthy lifestyle, interactive/conversational recommendations, etc.)
User modeling and representations (real-time user intent/style/taste modeling, combine with long term interest, incorporation of knowledge graph)
Architecture and infrastructure (novel and scalable deep learning architectures, steaming and event-driven processing, etc.)
Evaluations and explanations (evaluation, comparison, explanation of OARS for a recommendation task, off-policy and counterfactual evaluation, etc.)
Social and user impact (UX, welfare, and objectives of OARS, privacy and ethics considerations, etc.)

Submission Instructions:
==================
All papers will be peer reviewed (single-blind) by the program committee and judged by their relevance to the workshop, especially to the main themes identified above, and their potential to generate discussion.

All submissions must be formatted according to the ACM Conference Proceeding templates (two column format).

Submissions must describe work that is not previously published, not accepted for publication elsewhere, and not currently under review elsewhere. All submissions must be in English.

Please note that at least one of the authors of each accepted paper must register for the workshop and present the paper in-person.

Submissions to KDD OARS workshop should be made at https://easychair.org/my/conference?conf=oarskdd2023


ORGANIZERS:
==================
Xiquan Cui The Home Depot, USA
Vachik Dave Walmart Labs, USA
Yi Su UC Berkeley, USA
Julian McAuley UCSD, USA
Khalifeh Al-Jadda Google Inc, USA
Srijan Kumar Georgia Institute of Technology, USA
Tao Ye Amazon, USA
Stephen Guo Indeed, USA

Contact: Please direct all your queries to xiquan_cui@homedepot.com for help.

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