Resources
Recommender-System Software Libraries & APIs
There is a plethora of software libraries and APIs that often implement dozens of recommendation algorithms. In the Google Sheet below, you find a collection of recommender-system libraries and APIs (early draft / work-in-progress!). If you would like to add or change information, please send a request and provide us with some details about yourself....
List of RecSys Researchers
The Google Map below shows experts in the field of recommender systems. Our goal is to keep this map up-to-date with senior and active recommender-systems researchers. The map provides a good starting point for prospective Ph.D. students looking for potential supervisors; organizations and businesses looking for recommender-systems experts for joint projects or consultancy jobs, and...
Datasets
There are a plethora of recommender-system datasets, and, more generally, almost every machine learning dataset can be used for recommendation systems, too. The de-facto standard dataset for recommendations is probably the MovieLens dataset (which exists in multiple variations). Based on a small study that we conducted, 40% of all research papers at the ACM Recommender...
Computing Resources
Running recommender-system experiments may require significant computing resources. Especially memory-based approaches like kNN might need more memory than a normal desktop computer offers. Luckily, many organisations offer free or cheap (cloud) computing resources, though often limited in their free versions Cloud GPUs https://vast.ai/ claims to reduce GPU costs by factor 3-5 as they don´t offer...
Competitions, Challenges, Shared Tasks & Living Labs
To test your skills in recommender-system development and research, competitions, shared tasks, and living labs are ideal. Notable initiatives include Kaggle is the major platform for machine learning competitions, which includes many recommender-systems competitions. The ACM RecSys Challenge is co-hosted every year alongside the ACM RecSys conference. It is sponsored by major industry partners who...
Recommendations-As-a-Service (RaaS)
While recommender-system software libraries and APIs support you in developing a recommender system, a Recommender-System As-a-Service (RaaS) does all the work for you. Typically, you can integrate a recommender system into e.g. your e-commerce website or blog with a few clicks or lines of code. A RaaS comes with some compromises relating to flexibility, control...
Prizes & Awards
NVIDIA Team wins the ACM RecSys Challenge 2020 It seems that NVIDIA becomes a new big player in the recommender-system community. After introducing Merlin – a Framework for Deep Recommender Systems – and offering an online course for Building Intelligent Recommender Systems, a team of NVIDIA employees now won the ACM RecSys Challenge 2020. The...
https://Your-Project.Recommender-Systems.com
If you have a project related to recommender systems, we would be glad to support you with web space and a sub-domain like https://Your-Project.Recommender-Systems.com. Alternatively, you may get only a subdomain that forwards to your website at some other website host (e.g. GitHub or GoDaddy). If you are interested, please contact us, and let us...