A Cluster Adaptive Genetic Model for Improving the Recommender System
نویسنده
چکیده
Recommender System is a process or model that can be applied to identify the user choice based on some statistical observations. In this work, A movie recommender system is defined using cluster cluster adaptive genetic approach. In first phase of this model, the clustering is applied on user dataset to identify the most similar users. Later on, the statistical analysis is applied to generate the collaborative recommender statistics. Finally, the generated featured dataset is processed on genetic approach to identify the effective recommendation result. The work results shows that the method has reduced the error rate and improved the accuracy of recommender system.
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