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Let R talk to Myrrix. Myrrix is a complete, real-time, scalable clustering and recommender system, evolved from Apache Mahout.

This is the implementation for the paper: Sequential Recommender System based on Hierarchical Attention Network

Book recommender system utilizing collaborative filtering and Nearest Neighbors algorithms for personalized and popular reading suggestions

No description available from source.

This is the repository of our article published on MDPI Entropy "Feature Selection for Recommender Systems with Quantum Computing".

"End-to-End encryption is practically a meaningless phrase used by internet-based companies to coax people into believing the modern myth of online privacy."― Abhijit Naskar

Developed a recommendation system in Python using Netflix prize dataset and MovieLens data set using collaborative filtering technique to recommend movies to a user, based on their preferences.

Official code for "Enriching Semantic Profiles into Knowledge Graph for Recommender Systems Using Large Language Models" (KDD'26)

Hands-on Training for Recommender Systems

No description available from source.