Abstract
Recommendation System is able to help users to choose items, including movies, that match their interests. One of the problems faced by recommendation system is cold-start problem. Cold start problem can be categorized into three types, they are: recommending existed item for new user, recommending new item for existed user, and recommending new item for new user. Pairwise preference regression is a method that directly deals with cold-start problem. This method can suggest a recommendation, not only for users who have no historical rating, but also for those who only have less demographic info. From the experiment result, the best score of Normalized Discounted Cumulative Gain (nDGC) from the system is 0.8484. The standard deviation of rating resulted by the recommendation system is 1.24, the average is 3.82. Consequently, the distribution of recommendation result is around rating 5 to 3. Those results mean that this recommendation system is good to solving cold-start problem in movie recommendation system.
Highlights
THE great number of information availability and accessibility is impacted on the problem of how to filter the relevant information for users
It was because the data in partition II used data of existing item, as a result, the recommendation result was better than the recommendation of new item
The value of Normalized Discounted Cumulative Gain (nDCG) that was obtained for all partition was more than 0.83, it means that this recommendation system was good to solving cold-start problem [3]
Summary
THE great number of information availability and accessibility is impacted on the problem of how to filter the relevant information for users. Recommendation system emerges as one of the solutions in handling that problem by providing suggestion to help user in making decision [1]. Users rely on recommendation from another user, in the form of product review, news from social media or electronic media, survey, etc., to choose or buy a product, including choose a movie to watch. With the increasing number of available movies recently, causing the audiences need to be selective to choose movies that they would like to watch
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