I am now very interested in applying causal inference to the design of recommendation system algorithms. However, there are no good ideas yet, so if there are researchers who have a common interest in this area, we can discuss it together.
Arturo Geigel
Sun Xiao Xin ,
What would your approach be? Something along implementation of Bayesian Networks or more into basic research of ML for causal inference?
Regards
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Rob Christiaanse
Dear Sun Xiao Xin , I think this reserach will be of interest:
- Causal Inference for Recommender Systems, ACM ISBN 978-1-4503-7583-2/20/09 https://doi.org/10.1145/3383313.3412225
- Causal Inference for Recommendation, http://www.its.caltech.edu/~fehardt/UAI2016WS/papers/Liang.pdf
- Causality-Aware Neighborhood Methods for Recommender Systems https://arxiv.org/pdf/2012.09442.pdf
- A Survey of Deep Reinforcement Learning in Recommender Systems: A Systematic Review and Future Directions.J. ACM, Vol. 37, No. 4, Article 111. Publication date: September 2021.
KR
Rob
ps there is more to say about causality and (computational and mathematical) logic, but I think that is beyound your question
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Rahul Sharma
Hi I am working with Simpsons Paradox and XAI. You explore it and if it is interesting for you, we can collaborate.
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