The Association for Computing Machinery (ACM) has approved the proposal for a new journal, the “ACM Transactions on Recommender Systems“, in short, ACM TORS. I am delighted to be appointed as associate editor of the journal. ACM TORS is the first journal from a major publisher that solely focuses on recommender systems.
The proposal for the journal was inspired by a blog post that I wrote and eventually initiated by two of the leading researchers in recommender systems, Dietmar Jannach and Li Chen. I am honored to serve on the editorial board along with some of the most well-known figures in the recommender-system community.
Recommender systems are a type of machine learning algorithm that are designed to predict user preferences and make personalized recommendations. They are used in a variety of applications, such as e-commerce, social media, and content platforms, and are becoming increasingly important in today’s digital landscape. The field of recommender systems is rapidly evolving, with new advances in areas such as deep learning and explainable AI.
A dedicated journal for recommender systems was needed to provide a forum for researchers and practitioners to share their work and insights, and to stay informed about the latest advances in the field. The “ACM Transactions on Recommender Systems” (TORS) is one such journal, which was created to provide a venue for high-quality research papers, survey papers, and technical notes on the topic of recommender systems.
ACM, the Association for Computing Machinery, is a leading professional organization in the field of computer science. It was founded in 1947 and has since grown to be one of the largest and most prestigious computing organizations in the world. ACM has a number of publications, including journals, magazines, and conference proceedings, which are widely recognized as some of the most prestigious and influential in the field.
Having ACM as the publisher for a journal like TORS, is an indication of its high standards and reputation in the field of computer science. The journal is peer-reviewed and is considered a highly reputable source for the latest advances in recommender systems research. Being published in TORS can be a valuable addition to a researcher’s CV and can also help to promote their work to a wider audience.