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K-Means Demographic based Crowd Aware Movie Recommendation System
In this paper we put forward a novel technique of K-Means based crowd-aware recommender system in which we select the closest crowd to the particular user and locate the preference of those to suggest that user a set of movies at that time in the same province. K-Means is the clustering algorithm that is used to cluster the specifiedspot among the set of spots in the dataset. Here we make groups of the crowd and then locate in which cluster a particular user belongs. Following classify the user in particular category of the crowd, system will find the set of movies among the crowd, which is most preferred by that set of crowd in which the user is classified. The proposed approach is likely to attain the high precision, effectiveness and will take less time as judge against other techniques for movie recommendation.
movie recommendations, collaborDemographic Filtering, Hybrid, K-Means Clustering, Movie Recommendations.
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