ACM, the Association for Computing Machinery, has announced the launch of a new ACM journal: Transactions on Recommender Systems (TORS). Submissions are now being accepted through the publication’s submissions site. The inaugural issue will be published in Spring 2023 and issued on a quarterly basis going forward.
ACM Transactions on Recommender Systems (TORS) will publish high-quality papers that address various aspects of recommender systems research. The journal takes a holistic view of the field and calls for contributions from different subfields of computer science and information systems, such as machine learning, data mining, information retrieval, web-based systems, data science and big data, and human-computer interaction.
For example, the editors welcome papers on the latest algorithmic approaches to create, filter, and rank recommendations. To showcase the latest advances, papers that describe system architectures and their implementations will also be featured. Beyond purely technical considerations, research that investigates the role of human-computer interaction on decision-making, as well as papers that analyze the impact of recommender systems on users, organizations, and society, will also play a prominent role in the journal.
A special emphasis will also be placed on how systems are evaluated. TORS editors are encouraging the submission of papers that propose new ways of evaluating the effectiveness of recommender systems, such as new metrics, protocols, and user studies.
ACM publishes more than 60 scholarly peer-reviewed journals in dozens of computing and information technology disciplines. Available in print and online, ACM's high-impact, peer-reviewed journals constitute a vast and comprehensive archive of computing innovation, covering emerging and established computing research for both practical and theoretical applications. ACM journal editors are thought leaders in their fields, and ACM's emphasis on rapid publication ensures minimal delay in communicating exciting new ideas and discoveries.
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