Faculty Advisor

Rundensteiner, Elke A

Abstract

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.

Publisher

Worcester Polytechnic Institute

Date Accepted

May 2009

Major

Computer Science

Project Type

Major Qualifying Project

Accessibility

Unrestricted

Advisor Department

Computer Science

Share

COinS