RECSYS

Evaluation of recommender systems is a central activity when developing recommender systems, both in industry and academia. The second edition of the PERSPECTIVES workshop held at RecSys 2022 brought together academia and industry to critically reflect ...

Recommender systems are more and more often modelled as repeated decision making processes – deciding which (ranking of) items to recommend to a given user. Each decision to recommend or rank an item has a significant impact on immediate and future user ...

Recommender Systems are becoming an inherent part of today’s Internet. They can be found anywhere from e-commerce platforms (eBay, Amazon) to music or movie streaming (Spotify, Netflix), social media (Facebook, Instagram, TikTok), travel platforms (...

Modern online systems for user modeling and recommendation need to continuously deal with complex data streams generated by users at very fast rates. This can be overwhelming for systems and algorithms designed to train recommendation models in batches, ...

In the last few years, a renewed interest of the research community in conversational recommender systems (CRSs) has been emerging. This is likely due to the massive proliferation of Digital Assistants (DAs) such as Amazon Alexa, Siri, or Google ...

The constant increase in the amount of data and information available on the Web has made the development of systems that can support users in making relevant decisions increasingly important. Recommender systems (RSs) have emerged as tools to address ...

As organizations increasingly digitize their business processes, the role of recommender systems in work environments is expanding. The goal of the RecWork workshop is closing the gap in recommender systems research for work environments in areas such ...

The Workshop on Recommenders in Tourism (RecTour) 2022, which is held in conjunction with the 16th ACM Conference on Recommender Systems (RecSys), addresses specific challenges for recommender systems in the tourism domain. In this overview paper, we ...

Online Fashion retailers have significantly increased in popularity over the last decade, making it possible for customers to explore hundreds of thousands of products without the need to visit multiple stores or stand in long queues for checkout. ...

Recommendation systems are increasingly modelled as a sequential decision making process, where the system decides which items to recommend to a given user. Each decision to recommend an item or slate of items has a significant impact on immediate and ...

The 5th Workshop on Responsible Recommendation (FAccTRec 2022) was held in conjunction with the 16th ACM Conference on Recommender Systems on September, 2022 at Seattle, USA, in a hybrid format. This workshop brought together researchers and ...

The FinRec workshop series offers a central forum for the study and discussion of the domain-specific aspects, challenges, and opportunities of RecSys and other related technologies in the financial services domain. Six years after the second edition of ...

Contextual information has been widely recognized as an important modeling dimension in social sciences and in computing. In particular, the role of context has been recognized in enhancing recommendation results and retrieval performance. While a ...

The RecSys 2022 Challenge was a session-based recommendation task in the fashion domain. The dataset was supplied by Dressipi. Given session data consisting of views and purchases, as well as content data representing the fashion characteristics of the ...