Research, Develop & Publish

Recommender-System Software Libraries & APIs

There is a plethora of software libraries and APIs that often implement dozens of recommendation algorithms. We define a 'recommender-system software library' as e.g. a JAVA or Python library that you can easily integrate into your own application to run recommendation algorithms. Nevertheless, you still do need some recommender-system and programming knowledge to store data...

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Conferences

The premier conference for recommender systems research is the yearly ACM Conference Series on Recommender Systems. However, there are plenty of conferences more in the fields of information retrieval, machine learning, user modelling, and human-computer interaction that do publish research on recommender systems. The Google Sheets below lists the major conferences in the field of...

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Journals

CORE Conference Ranking 2020 Removes JCDL and other Digital Library Conferences from its Database The ACM/IEEE Joint Conference on Digital Libraries (JCDL) is the premier conference in the field of digital libraries and, besides the ACM RecSys, a good choice for publishing work related to research-paper recommender systems, citation recommenders, venue recommendation systems, reviewer assignment...

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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...

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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...

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Pre-Print Repositories

arXiv arXiv is probably the de-facto standard for publishing pre-prints in computer science. The major advantage of arXiv is that its content is included in many other services like academic recommender-systems, search engines, and open access meta-repositories like CORE. Hence, publishing at arXiv ensures a certain level of distribution of your manuscript. arXiv manuscripts are...

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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...

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Doctoral Consortiums

The ACM Recommender System Conference regularly hosts a doctoral consortium and so do many other major conferences in the field of related disciplines like information retrieval (SIGIR) and machine learning (e.g. AAAI, CIKM, ECAI. More details yet to come...

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Workshops

The ACM Conference on Recommender Systems always hosts a number of interesting workshops. An overview of past workshops can be found at https://recsys.acm.org/workshops/, for the most recent ones check the latest ACM RecSys Conference webpage. https://recsys.acm.org/workshops/ Many other conferences also host workshops relating to recommender systems. Most notably probably SIGIR and UMAP but also many...

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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...

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Data Repositories

More details yet to come...

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Code Repositories

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Web Page & Project Hosting

More details yet to come...

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State-of-the-Art Algorithms

"What are state-of-the-art recommendation algorithms?" is a question that should be a no-brainer to answer for any recommender-system researcher and developer. However, the answer is typical "I don't know, at least not for sure". The recommender-system community faces a reproducibility crisis, which makes it almost impossible to say what algorithms are truly state-of-the-art. In a...

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Events / Calendar

This calendar includes deadlines for conferences and workshops relating to recommender systems including some conferences relating to machine learning. Switch to the "Agenda" tab and select "Look for more" to see a list of all events or open the calendar in a New Browser Window. If you want to help us maintaining the calendar, please...

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‘Hot’ Research Topics

While 'Recommender Systems' is an established research discipline, the questions of how to generate good recommendations, what good recommendations are, and how to measure 'goodness' are far from being answered. To get an idea of 'hot' and promising research topics, have a look at the recent workshops of the ACM Recommender Systems conference, and other...

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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...

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Venue Rankings

News CORE Conference Ranking 2020 Removes JCDL and other Digital Library Conferences from its Database The ACM/IEEE Joint Conference on Digital Libraries (JCDL) is the premier conference in the field of digital libraries and, besides the ACM RecSys, a good choice for publishing work related to research-paper recommender systems, citation recommenders, venue recommendation systems, reviewer...

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