Recommender_system for movies and users

Fuzzy Genetic Approach to Recommender System

Project description

Implemented a hybrid fuzzy-genetic approach to recommender systems that retains the accuracy of memory-based collaborative Filtering(CF) and the scalability of model-based CF. project describes a new recommender system,which employs a genetic algorithm to learn personal preferences of users and provide tailored suggestions based on his previous preferences.

Crossover Used

Single point crossover

Mutation Used

Bit flip mutatations

Further Improvement

1. A hybrid model-based movie recommendation system which utilizes the improved K-means clustering coupled with genetic algorithms (GAs) on partition transformed user space.
2. Time can be reduse by using selection processes like
   1. Tournament selection.
   2. Roulette wheel selection
3. More formal techniques could be investicated for designing the fitness function in a sophisticated way.