AAAI Spring Symposium
on
Machine Learning in Information Access
Stanford, March 25-27, 1996 Marti Hearst and Haym Hirsh, co-chairs
mlia@parc.xerox.com
As the volume and importance of the information available on the Internet continues to increase, there is a growing interest in information access in all areas of computer science. This was the first professional gathering devoted to investigating the use of machine learning techniques to improve access to textual information. The goal of this symposium was to provide the much-needed opportunity to develop new ideas and a well-defined community in this growing field.
This symposium focused on new work in the application of machine learning techniques to information access problems, such as identifying interesting pages on the world wide web, text topic identification, and email filtering. The symposium included overviews of relevant aspects of both machine learning and information retrieval, and paper presentations discussing the use of machine learning in various information-access tasks. We were also pleased to have three guest speakers, speaking on the following topics:
Rik Belew has collected resources relevant to Machine Learning and Information Access .
Some symposium participants have put together suggestions of suggestions for research projects at the intersection of machine learning and information access.
Some Information Access Contact Points
Machine Learning in Information Access / Marti Hearst / hearst@parc.xerox.com Last modified: April 8, 1996