ACM SAC 2022 with “Track on Recommender Systems: Theory, User Interactions & Applications”
The 37th ACM/SIGAPP Symposium On Applied Computing (ACM SAC) has a dedicated track on recommender systems, like in many of the previous years. ACM SAC 2022 will be held in Brno, Czech Republic, April 25 – April 29, 2022.
The recommender-systems track is organized by
Yong Zheng, Illinois Institute of Technology, Chicago, USA
Markus Zanker, Free University of Bolzano, Italy
Li Chen, Hong Kong Baptist University, China
Panagiotis Symeonidis, University of the Aegean, Greece
Track on Recommender Systems
With the development of information technologies, human beings are more and more surrounded with floods of information, which further results in problems a person can have in understanding an issue or making decisions that can be caused by the presence of too much information. Recommender systems (RecSys) have proven to be helpful in alleviating this information overload problem, providing personalized services and assisting users’ decision making. The basic idea behind RecSys is to infer users’ tastes from their past behaviors (such as user ratings, purchases, reviews, click-throughs, etc). RecSys have been widely applied in a number of areas, including eCommerce (e.g., Amazon, eBay), movies (e.g., Netflix, Moviepilot), music (e.g., Pandora, Spotify), news (e.g., Yahoo news), tags (e.g., Flickr), social media (e.g., Twitter), online education (e.g., Coursera), and so forth.
The development of RecSys promotes various research topics, such as user interaction and interfaces, algorithm design and evaluations, computational efficiency, and recommendation explanations. As one of applied sciences, the field of recommender systems attracts experts and receives contributions from multidisciplinary areas, including Artificial Intelligence, Human Computer Interaction, Data Science, Decision Support Systems, Marketing, etc.
This track aims to provide a dedicated forum to researchers in RecSys and other applied computing areas for discussing the open research problems, solid solutions, latest challenges, novel applications and innovative research approaches in RecSys.
https://recsystrack.wordpress.com/
Stats on Submitted & Accepted Papers and Acceptance Rate at the ACM Recommender Systems Conference until 2023
More than a decade of the ACM RecSys Conference [Alan Said, 2017]
Call for Papers (CfP) of the 16th ACM Conference on Recommender Systems (ACM RecSys 2022)
About The Author
Joeran Beel
I am the founder of Recommender-Systems.com and head of the Intelligent Systems Group (ISG) at the University of Siegen, Germany https://isg.beel.org. We conduct research in recommender-systems (RecSys), personalization and information retrieval (IR) as well as on automated machine learning (AutoML), meta-learning and algorithm selection. Domains we are particularly interested in include smart places, eHealth, manufacturing (industry 4.0), mobility, visual computing, and digital libraries. We founded or maintain, among others, LensKit-Auto, Darwin & Goliath, Mr. DLib, and Docear, each with thousand of users; we contributed to TensorFlow, JabRef and others; and we developed the first prototypes of automated recommender systems (AutoSurprise and Auto-CaseRec) and Federated Meta Learning (FMLearn Server and Client).