ACM, the Association for Computing Machinery, today 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 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 on 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.
“We are especially excited that TORS will be a first-of-its-kind journal dedicated exclusively to recommender systems research," explained Co-EiC Dietmar Jannach, University of Klagenfurt (Austria). “TORS is launching at a very opportune time. As the impact of recommender systems continues to grow, more research is being published and more professionals are joining our ranks. This is all reflected in the annual ACM RecSys conference, which was recently elevated to an ‘A’ ranking by the popular CORE conference rankings list. TORS will add even more avenues for researchers to publish their work. Members of our community will be able to publish research beyond the page limits of the ACM RecSys conference, thus not being bound by conference submission deadlines.”
“Developing an effective recommender system requires input from computer science, as well as fields such as psychology and marketing,” added TORS Co-EiC Li Chen of Hong Kong Baptist University (China). “From the outset, we have envisioned TORS as a multidisciplinary journal. Our goal is to publish outstanding research related to recommender systems from a broad array of disciplines. At the same time, we are also flexible in terms of the format of the contributions we will accept. Of course, traditional research papers will be a cornerstone of TORS content, but we will also welcome survey papers, industry reports, reproducibility papers, opinion papers, and registered reports. We want this to be an outlet where people in research and industry can access the full spectrum of ideas that our field requires. We’re looking forward to using TORS as a platform for outstanding research that will move our field forward.”
In addition to Co-EiCs Chen and Jannach, the TORS editorial team is drawn from countries around the world. TORS Editorial Board Members include: Julian McAuley, UCSD (USA); Christine Bauer, Utrecht University (The Netherlands); Joeran Beel, University of Siegen (Germany); Robin Burke, University of Colorado (USA); Pablo Castells, Universidad Autónoma de Madrid (Spain); Guibing Guo, Northeastern University (Shenyang, China); George Karypis, University of Minnesota (USA); Bart Knijnenburg, Clemson University (USA); Joe Konstan, University of Minnesota (USA); Bamshad Mobasher, DePaul University (USA); Weike Pan, Shenzhen University (China); Francesco Ricci, Free University of Bolzano (Italy); Nava Tintarev, University of Maastricht (The Netherlands); Martijn Willemsen, TU Eindhoven (The Netherlands); Xing Xie, Microsoft Research Asia (China); Markus Zanker, Free University of Bolzano, Italy; Jie Zhang, NTU (Singapore); and Yongfeng Zhang, Rutgers University (USA).
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ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. ACM strengthens the computing profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.