Community Contributions

Advancing AI Through Research & Community

At Recombee, we believe in open innovation and collaborative advancement of AI technologies. Through RecombeeLab, our research division, we actively contribute to the scientific community by publishing state-of-the-art research, supporting PhD students, and openly sharing our methods.

Our partnerships with top universities and our commitment to open-source development reflect our mission to democratize advanced AI technologies.

Research Excellence

Through RecombeeLab, our joint research laboratory with the Faculty of Information Technology at the Czech Technical University in Prague, we're pushing the boundaries of recommendation systems and machine learning. We provide financial support to PhD students and actively collaborate on groundbreaking research projects.

Publications

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beeFormer: transformer for recommender systems

Improve recommendation of cold start items by training transformers on interactions.

Proceedings of the 18th ACM Conference on Recommender Systems

2024

Advanced popularity models for curiosity detection

Detecting and measuring popularity rates among loyal and curious audiences for online items.

Proceedings of the ACM Web Conference 2024

2024

Constrained matrix completion

Enhanced matrix completion methods with new constraints, improving prediction accuracy and efficiency through theoretical analysis and practical experiments.

41st International Conference on Machine Learning

2024

Context aware recommendation

Proposing a cognitive modeling approach that predicts selections from item triplets while providing interpretable context and item representations.

IEEE Transactions on Neural Networks and Learning Systems

2024

Open Source Projects

ELSA

Scalable linear shallow autoencoder for collaborative filtering.

Github

Repsys

Open-source framework for building and evaluating recommendation systems.

Github Demo

beeFormer

Advanced transformer architecture optimized for recommendation tasks.

Github

Community Engagement

We contribute as journal reviewers and serve on the program committees of major conferences.

Conference Support

Proud sponsor and co-organizer of major industry conferences including RecSys, contributing to the global advancement of recommendation systems research.

Non-Profit Collaboration

Supporting organizations like prg.ai and aidetem.cz in their mission to enhance education through AI-assisted personalization.

Making an Impact

Our commitment to open innovation and community support helps advance the field of AI while making cutting-edge technology accessible to researchers and developers worldwide.

Research Support

Funding PhD research and academic collaborations.

Open Source

Sharing advanced AI tools with the community.

Education

Supporting AI-driven educational initiatives.

Collaboration

Would you like to collaborate with us to push the boundaries of recommender systems? Are you interested in doing an industrial master’s or PhD thesis?