Group-Based Movie Recommendation System
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Computer Science and Electrical Engineering
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Computer Science
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Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission.
This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
Abstract
A recommendation system can be defined as a content-filtering system thatattempts to predict the likes or dislikes of a user. In the past many companies likeAmazon, Google, Netflix etc. have come up with competitive and efficient recom-mendation systems based on users past activities or profiles. The problem at handis to provide recommendations based on a group of individuals. The requirementfor such a system arises as people engage in various group activities. For example agame of cards, going out on a picnic, watching movies etc. During such activities,existing recommendation systems will provide recommendations based on only oneindividual which may or may not be enjoyable for the rest of the group. To solvethese issues, I have designed a group-based recommendation for movies