Based On Collaborative Filtering A Customized Movie Recommender Web Service Design And Implementation

Nowadays,the internet has entered the era of big data,a problem that human beings is facing is no longer too little information but information overload.Though the search engine has been very powerful,but with the keyword search,which only filteres the information for the users passively and does not take a initiative to collect user interested information.With the increasing demands,the recommendation engine has been appeared and developed rapidly.With keeping tracking and analyzing the preferences of the users,the recommendation engine can take the initiative to do the information recommendation to the users and keep amending with the feedbacks from the users until the users get satisfied recommendations.With collecting the metainformation of the users,the items,and the preferences and based on the analysis of demographic,content and collaborative filtering recommendation mechanism the recommendation system provides the preliminary recommendations,and then keeps amending with the feedbacks from the users until the users get satisfied recomendations.With the thorough research to the recommendation system,based on the mahout open-source recommendation engine a personalized movie recommendation web service is designed in this article.With collecting the preferences of the users,based on the similarity analysis between the audiences or the movies of the user-based collaborative filtering or item-based collaborative filtering this system provides the personalized recommendations.