SCoRS -- a content and collaborative based recommender system

Kogel, Wendy Elisabeth; Daniels, Brooke LeClair; St Yves, Christopher David

Student Work

SCoRS -- a content and collaborative based recommender system

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We designed and built a web-based movie recommender system. We used association rule mining to implement two data filtering methods. Content-based filtering identifies sets of common attributes of the movies that the user has liked in the past, while collaborative filtering associates users with each other based on similarities in taste. By combining content- and collaborative-base filtering, we obtained recommendations with a higher precision than either method individually.

This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

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