[fca-list] ACM RecSys 2023 - Second Call for Papers

** We apologize if you receive multiple copies of this CfP ** ** For the online version of this Call, visit: https://recsys.acm.org/recsys23/call/papers ** We are pleased to invite you to contribute to the 17th ACM Conference on Recommender Systems (RecSys 2023), the premier venue for research on the foundations and applications of recommendation technologies. The upcoming RecSys conference will be held on September 18–22, 2023 in Singapore, with an inclusive format that accommodates remote attendance. Each accepted paper is expected to be presented in person. The conference will continue RecSys’ tradition of connecting researchers, practitioners, and students to exchange ideas, frame problems, and share solutions across a range of specialties concerned with recommendation. All accepted papers will be published by ACM. We invite submissions of original research on all aspects of recommender systems, including contributions to: algorithms ranging from collaborative filtering to knowledge-based reasoning or deep learning; design ranging from studies of human preferences and decision-making to novel interaction design; systems including practical issues of scale and deployment; applications that bring forward the lessons of innovative applications across various domains from e-commerce to education to social connections; scientific inquiry on fundamental dynamics and impact of recommender systems. We welcome new research on recommendation technologies coming from diverse communities ranging from psychology to mathematics. In particular, we care as much about the human and economic impact of these systems as we care about their underlying algorithms. We encourage research papers coming from industry that focus on open challenges in their specific environment. Topics of interest for RecSys 2023 include but are not limited to (alphabetically ordered): * Algorithm scalability, performance, and implementations * Bias, fairness, bubbles, and ethics of recommender systems * Case studies of real-world implementations * Conversational and natural language recommender systems * Cross-domain recommendation * Data characteristics and processing challenges underlying recommender systems * Economic models and consequences of recommender systems * Interfaces for recommender systems * Multi-stakeholder recommendations * New aspects of recommender systems evaluation * Novel approaches to recommendation, including voice, VR/AR, etc. * Preference elicitation * Privacy and security * Socially- and context-aware recommender systems * Systems challenges such as scalability, data quality, and performance * User studies of recommendation applications Papers on demonstration for RecSys should be submitted to the demo track, while papers on new resources for RecSys should be submitted to the reproducibility track. They would be desk-rejected in the main track. We also point authors to the industry track for discussion of field experiences, deployments, user studies (etc.) that do not follow the framework of regular papers, or align with the reviewing guidelines below. A separate track is also provided for late-breaking results papers; this track is intended for short presentations of preliminary work, mainly focused on fostering discussions with other members of the RecSys community. Reviewing Process Reviewers will evaluate papers based on their significance, originality, rigor, and contribution to the field. In view of the RecSys conference goal of advancing the field, reviewers will also be asked to consider the replicability of the reported research. Replicability will be assessed in the context of the work itself — we recognize that a set of customer interviews (for example) may not be shareable, but the interview scripts can be provided along with other resources such as response coding protocols. Papers that are out of scope, incomplete, or lack sufficient evidence to support the basic claims, may be rejected without full review. Submission Guidelines LONG PAPERS should report on substantial contributions of lasting value. The maximum length is 16 pages including appendices (plus up to 2 pages of references). Each accepted long paper will be included in the conference proceedings and presented in a plenary session as part of the main conference program. SHORT PAPERS typically discuss exciting new work that is not yet mature enough for a long paper. In particular, novel but significant proposals will be considered for acceptance to this category despite not having gone through sufficient experimental validation or lacking strong theoretical foundation. Applications of recommender systems to novel areas are especially welcome. The maximum length is 8 pages including appendices (plus up to 2 pages references). Each accepted short paper will be included in the conference proceedings and presented either as an oral presentation or at the poster session. Note that rejected long paper submissions will not be considered as short papers. All submissions and reviews will be handled electronically. Papers must be submitted to easychair. EVALUATION AND REPRODUCIBILITY We always encourage authors to present reproducible scientific results and we strongly believe this is an attitude we should foster in our RecSys community. To promote a fair evaluation of new algorithms and approaches with state-of-the-art baselines and allow other researchers to reproduce the results presented in RecSys papers, we suggest the authors refer to one of the frameworks listed in https://github.com/ACMRecSys/recsys-evaluation-frameworks. As for the datasets to use in experimental evaluations, authors may refer to the repositories available at https://github.com/ACMRecSys/recsys-datasets. Sharing of datasets and code is encouraged, and authors presenting work that was tested on proprietary data may wish to include a secondary analysis on a public or shareable data set. We also strongly recommend the authors, unless there are restrictions, to make their code available on a public repository. The same holds for non-public datasets used for experimental evaluations. To keep the anonymity of their submission, the authors may refer to https://anonymous.4open.science/. FORMATTING ACM’s archival publication format separates content from presentation in the Digital Library to enhance accessibility and improve the flexibility and resiliency of our publications. Following the ACM publication workflow, all authors should submit manuscripts for review in a single-column format. Instructions for Word and LaTeX authors are given below: * Microsoft Word: Write your paper using the Submission Template (Review Submission Format). Follow the embedded instructions to apply the paragraph styles to your various text elements. The text is in single-column format at this stage and no additional formatting is required. * LaTeX: Please use the latest version of the Primary Article Template – LaTeX to create your submission. You must use the “manuscript” option with the \documentclass[manuscript,anonymous]{acmart} command to generate the output in a single-column format which is required for review. Please see the LaTeX documentation and ACM’s LaTeX best practices guide for further instructions. To ensure 100% compatibility with The ACM Publishing System (TAPS), please restrict the use of packages to the whitelist of approved LaTeX packages. A document with some frequently asked questions can be found here. Authors are strongly encouraged to provide “alt text” (alternative text) for floats (images, tables, etc.) in their content so that readers with disabilities can be given descriptive information for the floats that are important to the work. The descriptive text will be displayed in place of a float if the float cannot be loaded. This benefits the author as well as it broadens the reader base for the author’s work. Moreover, the alt text provides in-depth float descriptions to search engine crawlers, which helps to properly index these floats. Additionally, authors should follow the ACM Accessibility Recommendations for Publishing in Color and SIG ACCESS guidelines on describing figures. Should you have any questions or issues going through the instructions above, please contact support at acmtexsupport(a)aptaracorp.com for both LaTeX and Microsoft Word inquiries. Accepted papers will be later submitted to ACM’s production platform where authors will be able to review PDF and HTML output formats before publication. ANONYMITY The peer review process is mutually anonymous (double-blind). This means that all submissions must not include information identifying the authors or their organization. Specifically, do not include the authors’ names and affiliations, refer to your previous work in the third person (e.g., “Di Noia and Zhang (2023) recommended that RecSys submissions be anonymized by referring to the authors’ prior work in the third person.”), and avoid providing any other information that would allow reviewers to identify the authors, such as acknowledgments of individuals and funding sources. However, it is acceptable to explicitly refer in the paper to the companies or organizations that provided datasets, hosted experiments or deployed solutions if there is no implication that the authors are currently affiliated with the mentioned organization. Reviewers will be instructed not to search for tech reports, pre-prints, and other information about your research. Your responsibility is focused on making sure that the paper submission itself does not reveal your identity as an author. ETHICAL REVIEW FOR HUMAN-SUBJECTS RESEARCH ACM RecSys expects all authors to comply with ethical and regulatory guidelines associated with human subjects research, including research involving human participants and research using personally identifiable data. Papers reporting on such human subjects research must include a statement identifying any regulatory review the research is subject to (and identifying the form of approval provided), or explaining the lack of required review. Reviewers will be asked to consider whether the research was conducted in compliance with applicable ethical and regulatory guidelines. We encourage authors to consider further ethical implications and broader impacts of their work, and to discuss these in an appropriate section of their papers; “A Guide to Writing the NeurIPS Impact Statement” provides non-binding guidance on some of the kinds of things authors may wish to consider. ORIGINALITY Each paper should not be previously published or accepted to any peer-reviewed journal or conference, nor currently under review elsewhere (including as another paper submission for RecSys 2023). Papers published in workshop proceedings may only be submitted if the RecSys submission includes at least 30% substantially new approaches and results; such papers must also reference the original workshop paper in the submission form (but not in the anonymized paper). Papers that include text generated from a large-scale language model (LLM) such as ChatGPT are prohibited unless this produced text is presented as a part of the paper’s experimental analysis. AI tools may be used to edit and polish authors’ work, such as using LLMs for light editing of their own text (e.g., automate grammar checks, word autocorrect, and other editing work), but text “produced entirely” by AI is not allowed. For RecSys 2023, we adhere to the principles and guidelines stated in the LLM policy @ ICML 2023. PLAGIARISM Plagiarized papers will not be accepted for RecSys 2023. Our committees will be checking the plagiarism level of all submitted papers to ensure content originality using an automated tool. If you reuse non-novel text from a prior publication (e.g., the description of an algorithm or dataset), please make sure to cite the prior publication as the source of that text. If you have questions about reuse of text or simultaneous submission, please contact the program chairs at least one week prior to the submission deadline. Please refer to the ACM Publishing License Agreement and Authorship Policy for further details. Papers violating any of the above guidelines are subject to rejection without review and cases may be referred to the ACM Publications Ethics and Plagiarism committee for further action where warranted. PATENTING Please take note that the official publication date is the date the proceedings are made available in the ACM Digital Library. This date may be up to two weeks prior to the first day of the conference. The official publication date affects the deadline for any patent filings related to published work. SIGCHI Submitter Agreement RecSys 2023 is a SIGCHI conference and making a submission to a SIGCHI conference is a serious matter. Submissions require time and effort by SIGCHI volunteers to organize and manage the reviewing process, and, if the submission is accepted, the publication and presentation process. Thus, anyone who submits to RecSys 2023 implicitly confirms the following statements: 1. I confirm that this submission is the work of myself and my co-authors. 2. I confirm that I or my co-authors hold copyright to the content, and have obtained appropriate permissions for any portions of the content that are copyrighted by others. 3. I confirm that any research reported in this submission involving human subjects has gone through the appropriate approval process at my institution. 4. I confirm that if this paper is accepted, I or one of my co-authors will present the paper at the conference, either in person or through a conference-designated remote presentation option. Papers that are not presented at the conference by an author may be removed from the proceedings at the discretion of the program chairs. Important Dates * [LONG] Abstract submission deadline: April 14th, 2023 * [LONG] Paper submission deadline: April 21st, 2023 * [SHORT] Abstract submission deadline: May 2nd, 2023 * [SHORT] Paper submission deadline: May 9th, 2023 * Author notification [LONG and SHORT]: June 28th, 2023 * Camera-ready version deadline: July 26th, 2023 Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone. Program Chairs * Tommaso Di Noia, Polytechnic University of Bari (POLIBA), Bari, Italy * Min Zhang, Tsinghua University (THU), Beijing, China * E-mail: program2023(a)recsys.acm.org