Adaptive Information Filtering with Minimal Instruction MIT 2000-08 Progress Report : January 1 , 2002 — June 30 , 2002 Tommi Jaakkola and Tomaso Poggio Project Overview
This project concerns with automated methods for finding a few pieces of relevant information (such as research articles) within a large dataset of predominantly incomplete and superficially similar information (such as technical report archives). While many such information filtering tasks vary considerably depending on the context, the primary challenges associated with automated techniques are often shared across different tasks. In this project, we develop the foundations for adaptive information retrieval tools with the ability to function accurately with minimal instruction of what is relevant, learn from related filtering problems, and make use of any optional feedback automatically queried from the user