Distributing information for collaborative filtering on Usenet Net News
David A. Maltz · DSpace@MIT (Massachusetts Institute of Technology) · 1994
As part of the "Information Revolution," the amount of raw information available to computer users has increased as never before. Unfortunately, there has been a corresponding jump in the amount of unrelated information users must search through in order find information of interest. Harnessing the power of multiple users to form a collaborative filter provides a robust way of helping direct users to the information that will be most useful to them. To test this idea, we have designed a large scale collaborative filtering system tuned to help users extract information from Usenet Net News. In this thesis we demonstrate a system for collaborative filtering that can scale up to encompass the large distributed information sources of which Usenet Net News is an example. Our system provides varying levels of anonymity to protect the interests of the users, as well as means of minimizing the load placed on the existing information source. We believe the system will be especially good at thre...