CfP: ACM TORS Special Issue on Recommender Systems in Industry – New Challenges and Opportunities

ACM Transactions on Recommender Systems (ACM TORS) is inviting submissions to a special issue on Recommender Systems in Industry: New Challenges and Opportunities, edited by Dietmar Jannach and Li Chen. The submission deadline is March 1, 2027.

The subject is what happens when recommender systems are used in practice. Data arrives incomplete and keeps changing, business objectives compete, systems have to scale, and online results do not always match offline evaluations. Even improvements in recommendation accuracy may say little about the actual value delivered to users or businesses. Many of these challenges only become fully apparent in real-world deployments.

The ACM RecSys conference has long reflected the close relationship between academia and industry. It has a dedicated Industry Track, the annual RecSys Challenge, numerous corporate sponsors, and substantial participation from industry practitioners. According to the conference organizers, around 60% of attendees come from industry. The Industry Track at RecSys 2026 alone received 306 submissions.

It is good to see TORS continuing to give dedicated attention to industrial practice as well. This is now already the second special issue — the first one was just published recently.

One detail in the call deserves particular attention. Industry reports do not necessarily need to introduce a new algorithm or provide a detailed technical exposition. The editors want to understand the real-world problem, how it was addressed, and what others can learn from the experience. Most reports are expected to be around 10–20 pages, although there is no strict page limit. Significantly extended versions of previously published RecSys Industry Track papers are also welcome.

The range of topics is broad. It includes industry case studies, success and failure stories, academia–industry collaborations, measuring business and consumer value, the gap between offline and online evaluation, data engineering, scalability, recommendation biases, the use of LLMs in real applications, privacy and security, and organizational challenges.

Important Dates

• Submission deadline: March 1, 2027
• First-round review decisions: June 1, 2027
• Revised submissions: August 1, 2027
• Final decisions: September 1, 2027

Manuscripts should follow the ACM TORS submission guidelines and be submitted through Manuscript Central. Authors should obtain company approval in advance where necessary.

The real opportunity is to make experiences from deployed recommender systems available to the research community. Success stories matter, but failed approaches, operational constraints, and unexpected results can be just as valuable for identifying new research questions. Hopefully, this special issue will encourage more industry practitioners to share those lessons.