Date of Award

12-2004

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Committee Director

Johan Bollen

Committee Member

Kurt Maly

Committee Member

Michael Nelson

Committee Member

Mohammad Zubair

Call Number for Print

Special Collections LD4331.C65 A73 2004

Abstract

Many recommender systems exist today to help users deal with the large growth in the amount of information available in the Internet. Most of these recommender systems use collaborative filtering or content-based techniques to present new material that would be of interest to a user. While these methods have proven to be effective, they have not been designed specifically for multimedia collections. In this study we present a new method to find recommendations that is not dependent on traditional Information Retrieval (IR) methods and compare it to algorithms that do rely on traditional IR methods. We evaluated these algorithms using an open source video test collection. Our study shows that our proposed approach outperforms a collaborative filtering algorithm and performs just as well as an algorithm that uses the Vector Space Model to find recommendations.

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In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

DOI

10.25777/2866-4j44

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