Recommendation systems are a staple of Web 2.0. Sites such as Amazon.com and Netflix, for example, use recommendation systems to suggest products to customers. Currently, most of these systems involve looking at numerical ratings to judge user interest. These methods are effective, but they do not take into account the context in which the users rated the objects. This project aims to develop a tag based recommendation system to take context into account. Popular websites such as del.icio.us and Citeulike.org already use this data model, but do not generate recommendations from it.The specific goal is to recommend academic papers to researchers.

• 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.

Creator

• Bentley, Jordan H

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-050109-062713

Advisor

• Rundensteiner, Elke A.

Year

• 2009

Date created

• 2009-05-01

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright

Last modified

• 2020-12-31