Learning to Create Customized Authority Lists

The proliferation of hypertext and the popularity of Kleinberg's HITS algorithm have brought about an increased interest in link analysis. While HITS and its older relatives from the Bibliometrics provide a method for nding authoritative sources on a particular topic, they do not allow individual users to inject their own opinions on what sources are authoritative. This paper presents a technique for learning a user's internal model of authority. We present experimental results based on Cora on-line index, a database of approximately one million on-line computer science literature references.

• Type: Conference
• Year: 2000
• Where: ICML
• Authors: Huan Chang, David Cohn, Andrew McCallum
• Keywords: Authoritative Sources, Cora On-line Index, ICML 2000, Machine Learning, Science Literature References