Faculty Advisor

Claypool, Mark L.

Abstract

This project determined the possible benefits of using an online personalized filtering system for paper greeting cards at Sparks.com. A test recommender system was developed in Java that implemented content-based and collaborative filtering algorithms. Additionally, a combination of these filtering algorithms was created to see if this approach gave more accurate results. Using information extracted from their purchase history database, the system was tested against other methods for displaying cards that do not utilize personalized filtering. We found that using content-based, collaborative or top 10 approach will result in highly accurate predictions compared to the random ordering of cards currently done at Sparks.com.

Publisher

Worcester Polytechnic Institute

Date Accepted

January 2000

Major

Computer Science

Project Type

Major Qualifying Project

Accessibility

Restricted-WPI community only

Advisor Department

Computer Science

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