The 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP) will take place in Cagliari, Italy from Monday, July 1 2024 – Thursday, July 4 2024. The following calls for contribution are still open for submission.
The theme of ACM UMAP 2024 is “Collaboration and Cooperation for the Greater Good”. Specifically, we welcome submissions that highlight the impact that working together and synergy (such as between academia, industry, influential policymaking bodies, committees and communities) can have on solving the world’s biggest problems; the focus is on investigations that capture how user modeling, personalization, and adaptation of (intelligent) systems, also with the use of large language models and generative AI, may influence user behavior, trustful processes and whether new models are required, for building sustainable and inclusive services and solutions that can address critical challenges of our world.
While we encourage submissions related to this theme, the scope of the conference is not limited to the theme only. As always, contributions from academia, industry, and other organizations discussing open challenges or novel research approaches are expected to be supported by rigorous evidence appropriate to claims (e.g., user study, system evaluation, computational analysis).
Please refer to the following deadlines, when submitting:
More details can be found here.
Doctoral students are invited to apply for presenting their research to experienced scholars who will provide constructive feedback and advice. Students should consider participating in the DC if they are at least one year away from completing their dissertation at the time of the event, but after having settled on a research area or dissertation topic.
Please refer to the following deadline, when submitting:
Further details regarding this call can be found here.
Tutorials are expected to be instructional sessions aimed to provide a comprehensive introduction to established or emerging research topics of interest for the UMAP community. An ideal tutorial should be broad enough to provide a basic introduction to the chosen area, but it should also cover the most important topics in depth. Tutorials are encouraged to be as dynamic and interactive as possible.
Please refer to the following deadline, when submitting:
For additional information, please refer to the conference's website.
ACM UMAP 2024 is pleased to invite proposals for workshops to be held in conjunction with the conference. Please consult the ACM UMAP 2024 general call for full and short papers concerning the key topics of this call as well.
In the 32nd edition of ACM UMAP, the goal is to have a balanced workshop program, comprising different workshop formats and combining newly emerging, currently evolving, and established research topics. Workshops are encouraged to be as dynamic and interactive as possible. Different full-day and half-day workshop schemas are possible. For more information, please refer to the conference's website.
The deadline is as follows:
HT’24 is open to a range of submission formats, from long and short papers to demos and artworks to panels, posters, tutorials and workshops.
The topic of this edition is Creative Intelligence. The community is invited to reflect on the role of interactive, intelligent hypermedia in supporting, enhancing, and communicating creative work. The tagline “Creative Intelligence” gives an opportunity to reflect on hypertext works, systems and communities that employ digital media in an inventive way that we encourage to understand not only as ground-breaking but also rule-breaking. We welcome reflections on phenomena that in various ways defy industry standards to deliver their creative stance and leave a lasting impact.
The conference features five research tracks and three practitioner tracks. Furthermore, requests for hosting workshops and training sessions are welcome.
If you would like to contribute to the conference by submitting, please refer to the following deadlines:
WebSci and SIGWEB are pleased to announce the availability of a fund to help support attendance to WebSci 2023 in Austin, TX, USA.
WebSci’23 travel grants provide support up to $1,500 for students, early career scholars and other presenters from underrepresented regions, who have an accepted paper at the conference and submit scholarship applications by March 26, 2023. In the event that scholarship applications exceed available funds, preference will be given to presenters from underrepresented regions who are planning to attend the whole Web Conference. This fund offsets travel costs but won't cover registration.
To apply for the Travel Grant Program, please complete the online application at the link below no later than March 26, 2023. Notifications will be sent by March 31.
WebSci free online tickets are intended to help students to attend the conference virtually. In the event that requests exceed available tickets, preference will be given to students who are presenting a paper and those who are from underrepresented regions. To apply for a free ticket, please complete the online application at the link below by March 26, 2023.
To apply for either kind of support, kindly submit this very simple form: https://forms.gle/pLvQg7vjwYpXieXLA
This year WebSci’23 is co-located with The Web Conference, with both taking place in Austin, Texas. WebSci’23 will take place on Sunday, April 30 and Monday, May 01. To participate in the WebSci’23 conference, you may choose to either register for WebSci-only at a rate of $100 for virtual participation or $450 early-bird rate for in-person participation, or register for The Web Conference, which allows for participation in WebSci’23 at no additional costs. For WebSci’23, there is only one rate for ACM members, non-ACM members, and students.
Registration is open and may be started here. For any enquiries regarding registration, please contact
In other exciting news, WebSci and SIGWEB have agreed to support students and early career scholars via travel grants and free online tickets. Details on the criteria and application procedures will be shared via mail updates and our social media channels soon, so stay tuned for this!
While we are still working on the last aspects of the conference program and the exact timings, we can promise you two conference days packed with interesting events, including keynotes by Dhiraj Murthy and David Rand (shared with The Web Conference) and attendance at The Web Conference’s keynote talk by Bob Metcalfe. WebSci’23 will close with an expert panel on Monday evening.
Front and center of the conference will, as always, of course be the authors and their submissions, discussing all aspects of this year’s theme Inequalities in the Face of Concurrent Crises. WebSci’23 will therefore have paper sessions on the full range of Web Science topics, approaching the theme from different perspectives - from Online Communities and Digital Analytics and Language and Emotions to sessions on Politics and Ideology, Harmful and Problematic Behavior, and Misinformation and Misperceptions. Over the coming weeks, we will present the individual paper sessions in more detail.
For this and everything else #WebSci23, keep an eye on the hashtag on social media, and check our website for further updates.
We are excited to announce 27 accepted tutorials at #TheWebConf 2023. The conference will take place in Texas, USA on April 30 - May 4 2023. See the complete list with teaser videos at https://www2023.thewebconf.org/program/tutorials/.
Internet Advertising to Improve Public Health: Opportunities and Challenges
Elad Yom-Tov, Liat Levontin, Ingmar Weber and Manuela Fritz.
Trustworthy Recommender Systems
Wenqi Fan, Xiangyu Zhao, Lin Wang, Xiao Chen, Jingtong Gao and Qidong Liu.
Data-Informed Interaction Learning
Behrooz Omidvar-Tehrani and Sihem Amer-Yahia.
Graph Neural Networks: Foundation, Frontiers and Applications
Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao and Xiaojie Guo.
Mining of Real-world Hypergraphs: Patterns, Tools, and Generators
Geon Lee, Jaemin Yoo and Kijung Shin.
Practical Bandits: An Industry Perspective
Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari and Devesh Parekh.
Same Data, Different Model: Choosing an Ontology Modeling Methodology
Cogan Shimizu, Torsten Hahmann and Hande McGinty.
Graph Neural Networks for Tabular Data Learning
Cheng-Te Li, Yu-Che Tsai and Jay Chiehen Liao.
Conversational Information Seeking: Theory and Application
Jeffrey Dalton, Filip Radlinksi, Federico Rossetto, Hamed Zamani and Johanne Trippas.
Tutorial: Declarative Web Applications with XForms
Steven Pemberton.
Tutorial: Invisible Markup
Steven Pemberton.
Catch Me If You GAN: Generation, Detection, and Obfuscation of Deepfake Texts
Adaku Uchendu, Thai Le and Dongwon Lee.
Towards Next-Generation Intelligent Assistants for AR/VR Devices
Xin Luna Dong, Seungwhan Moon, Yifan Xu and Zhou Yu.
Fairness in Ranking: From Values to Technical Choices and Back
Julia Stoyanovich, Meike Zehlike and Ke Yang.
Lecture-style Tutorial: Causal AI for web and health care
Utkarshani Jaimini, Usha Lokala, Kaushik Roy and Amit Sheth.
Turning Web-Scale Texts to Knowledge: Transferring Pretrained Representations to Text Mining Applications
Yu Meng, Jiaxin Huang, Yu Zhang and Jiawei Han.
The Advantages of Adding Noise
Reyhaneh Abdolazimi and Reza Zafarani.
Advances in Simulation Technology for Web Applications
Da Xu, Shuyuan Xu, Bo Yang and Yongfeng Zhang.
Model Monitoring in Practice: Lessons Learned and Open Challenges
Krishnaram Kenthapadi, Himabindu Lakkaraju, Pradeep Natarajan and Mehrnoosh Sameki.
Continual Graph Learning
Xikun Zhang, Dongjin Song, Yushan Jiang, Zijie Pan and Dacheng Tao.
Never-Ending Learning, Lifelong Learning and Continual Learning in the Era of Large Pre-Trained Language Models
Estevam Hruschka.
Multi-Modal Recommender Systems: Towards Addressing Sparsity, Comparability, and Explainability
Trung-Hoang Le, Quoc-Tuan Truong, Aghiles Salah and Hady Lauw.
Lifelong Learning Cross-domain Recommender Systems
Liang Hu, Shoujin Wang, Qi Zhang and Usman Naseem.
Towards Out-of-Distribution Generalization on Graphs
Xin Wang, Haoyang Li and Wenwu Zhu.
Spoken Language Understanding for Conversational AI: Recent Advances and Future Direction
Soyeon Han, Siqu Long, Henry Weld and Josiah Poon.
Self-supervised Learning and Pre-training on Graphs
Yukuo Cen, Yuxiao Dong and Jie Tang.
When Sparse Meets Dense: Learning Advanced Graph Neural Networks with DGL-Sparse Package
Minjie Wang, Hongzhi Chen, Quan Gan, George Karypis and Zheng Zhang.