Types of Publications
We welcome publications at all levels of complexity - from student projects to cutting-edge research. What matters is the clarity of presentation and potential value to the community. The following are various types of publications we welcome.
Research & Development:
- Research papers presenting novel recommendation approaches
- Research summaries synthesizing recent advances in the field
- Benchmark studies comparing different recommendation models
- Dataset contributions with annotated recommendation data
- Replication studies of notable papers
Implementation & Applications:
- Industrial applications and deployment case studies
- Implementation guides and best practices
- System architecture and scalability studies
- Kaggle competition solution write-ups and analyses
Open Source & Independent Projects:
- Open-source recommendation libraries and packages
- Tools and utilities for recommender systems
- Personal exploration projects and experiments
- Side projects testing novel approaches
- Customized implementations of research papers
Educational & Academic:
- Student projects and academic implementations
- Course projects and assignments
- Educational resources and learning materials
- Practical tutorials and hands-on guides
Maximize Your Chances of Being Featured
To create a publication that stands out in the recommender systems space, we highly recommend reviewing our comprehensive best practices guide before starting your publication. The guide will help you:
- Select the most suitable format for your RecSys project, whether it's a novel algorithm implementation, evaluation framework, or real-world case study
- Document your recommendation pipeline effectively, from data preprocessing and feature engineering to model architecture and evaluation metrics
- Demonstrate crucial aspects like scalability, real-time performance, and handling of cold-start problems
- Present offline and online evaluation results clearly, including key metrics like NDCG, MAP, and user engagement statistics
- Effectively communicate your system's impact on business metrics and user experience
Access our complete best practices guide here: Engage and Inspire: Best Practices for Publishing on Ready Tensor
Remember: Great RecSys publications often balance technical depth with practical insights. Share not just your model architecture, but also the challenges you encountered and how you addressed them in production.