REFEREE: An Open Framework for Practical Testing of Recommender Systems using ResearchIndex

Automated recommendation (e.g., personalized product recommendation on an ecommerce web site) is an increasingly valuable service associated with many databases--typically online retail catalogs and web logs. Currently, a major obstacle for evaluating recommendation algorithms is the lack of any standard, public, real-world testbed appropriate for the task. In an attempt to fill this gap, we have created REFEREE, a framework for building recommender systems using ResearchIndex--a huge online digital library of computer science research papers--so that anyone in the research community can develop, deploy, and evaluate recommender systems relatively easily and quickly. ResearchIndex is in many ways ideal for evaluating recommender systems, especially so-called hybrid recommenders that combine information filtering and collaborative filtering techniques. The documents in the database are associated with a wealth of content information (author, title, abstract, full text) and collaborativ...

• Type: Journal
• Year: 2002
• Where: VLDB
• Authors: Dan Cosley, Steve Lawrence, David M. Pennock
• Keywords: Database, Ecommerce Web Site, Recommender Systems, So-called Hybrid Recommenders, VLDB 2002