Call for Paper
Most
of the recent progress in information retrieval (IR) and recommender
systems has been fueled by deep learning. However, algorithmic advances
on accurate predictions and improved user modeling are just a small part
of designing considerations of a much larger system. IR and recommender
systems differ from other machine learning domains because they are
inherently part of an ecosystem -- in the simplest case, a world of
items and users. In these ecosystems, system designers face a broad
range of decisions -- e.g., how to balance popularity, which incentives
should be given to which users, or what safeguards to put in place to
ensure the platform thrives in the long-run.
Our
workshop aims to unite interested scholars, researchers, practitioners
and engineers from various industries and disciplines for a
comprehensive discussion of emerging challenges and promising solutions.
We hope to inspire research ideas, frameworks, applications,
experiments, as well as business incentives. The topics of interest
include but not limited to:
- Emerging
issues, challenges, and case studies on using decision-making
strategies in information retrieval and recommender systems
- User-centric metric and evaluation for decision making
- Designing and optimizing online or user experiments for search and recommender systems
- Theory and methodology for sequential decision making
- Frameworks or end-to-end solutions for decision making in large-scale production systems
- General topics on learning and inference with feedback systems
- Human-in-the-loop development of decision-making strategies
- Algorithmic accessibility, fairness, inclusiveness, and bias for information retrieval and recommender systems
- Research
proposals and problem statements for using techniques from other fields
(e.g. econometrics, public health) to address search and recommendation
problems
- Simulation and synthetic data analysis for decision making
Important Dates
- Open for Submission: Dec.15, 2022
- Submission deadline: Feb.6, 2023
- Notification of final decisions: Mar. 6, 2023
- Camera-ready version submission: Mar 20, 2023
- Workshops at WWW’23: April 30 and May 1, 2023
Submission Guidelines:
All
the accepted submissions will be presented at the workshop, either in
oral sessions or the poster session, and will be included in the
conference proceedings. We invite quality research contributions and
application studies in different formats:
- Original research papers, both long (limited to 8 content pages) and short (limited to 4 content pages)
- Extended abstracts for vision, perspective, and research proposal (4 content pages)
- Posters or demos on decision making systems (4 content pages)
- Workshop
papers that have been previously published or are under review for
another journal, conference or workshop should not be considered for
publication. Workshop papers should not exceed 12 pages in length
(maximum 8 pages for the main paper content + maximum 2 pages for
appendixes + maximum 2 pages for references). Papers must be submitted
in PDF format according to the ACM template published in the ACM
guidelines, selecting the generic “sigconf” sample. The reviewing
process is double- blinded, and authors can submit the manuscripts via Easychair (https://easychair.org/conferences/submissions?a=29997336)
Organizers: Da Xu (LinkedIn), Tobias Schnabel (Microsoft Research), Xiquan Cui (Home Depot), Sarah Dean (Cornell University), Jianpeng Xu (Walmart Labs), Aniket Deshmukh (Amazon), Bo Yang (Amazon).
For any questions or further information, please contact Da Xu (daxu...@gmail.com).