2 repository-uri
Awesome GitHub RepositoriesPreference Modeling
The process of creating mathematical models to represent and predict a user's latent interests.
Distinct from User Preference Settings: Focuses on the algorithmic modeling of interests rather than the UI for managing user settings.
Explore 2 awesome GitHub repositories matching user interface & experience · Preference Modeling. Refine with filters or upvote what's useful.
Awesome Preference Modeling GitHub Repositories
Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
- datawhalechina/team-learning-rs
datawhalechina/team-learning-rs
7,180Vezi pe GitHubThis project is an end-to-end recommendation pipeline and framework designed for building generative recommendation engines. It utilizes large language models and vector search to facilitate personalized item discovery and produces item recommendations through tokenization and semantic alignment. The system integrates a generative recommendation engine with a multi-objective ranking system and a vector search retrieval pipeline. These components allow for the use of reasoning frameworks to perform inference over items and the application of re-ranking algorithms to optimize the diversity of t
Predicts user interests using multi-objective modeling and feature crossing to rank candidates precisely.
Python - hexiangnan/neural_collaborative_filtering
hexiangnan/neural_collaborative_filtering
1,885Vezi pe GitHubNeural collaborative filtering is a recommendation system framework that predicts user item preferences from implicit feedback by combining generalized matrix factorization and multi-layer perceptron networks through a shared final embedding layer. It captures both linear and non-linear interactions to model user preferences from historical data. The framework executes training and evaluation runs through a configuration-driven pipeline accessible via command-line interfaces, parsing hyperparameters such as learning rates, batch sizes, and latent dimensions. It optimizes implicit feedback mod
Combines generalized matrix factorization and multi-layer perceptron approaches to learn user preference interactions.
Pythoncollaborative-filteringdeep-learningrecommender-system
