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A Context Aware Recommendation System for movies

Le, Tan Quach
Master thesis
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URI
http://hdl.handle.net/11250/2446511
Date
2017
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  • Institutt for datateknologi og informatikk [5024]
Abstract
People like to watch movies, but they do not always know what they want to

see. Although there exist applications that helps people solve this issue, they

are not being used very often (see Appendix A). People tend to do their own

research to decide what to wach. This thesis will be looking into this issue and

provide a proof of concept prototype. Not only does the prototype recommend

movies, but it also introduces an social feature that can be extended to so much

more. This feature were found by doing a round of interviews, while trying to

nd the cause of why people do not use the recommendation systems.

The thesis describes some of the state of the art approaches to recommenda-

tion system algorithms and the implementation of the prototype. The prototype

was evaluated by its accuracy and speed using data sets from Movielens.

The results show that the chosen approach to recommendation systems is

viable, and that the accuracy of the recommendation is not the only reason that

recommendation systems are not being used that much. The results show that

a social feature might increase the use of recommendation systems.
Publisher
NTNU

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