Autonomous Document Classification for Business
Research Note, RN/96/48. University College London, Computer Science, Gower Street, London, WC1E 6BT, UK, (June 1996)Abstract
With the continuing exponential growth of the Internet
and the more recent growth of business Intranets, the
commercial world is becoming increasingly aware of the
problem of electronic information overload. This has
encouraged interest in developing agents/softbots that
can act as electronic personal assistants and can
develop and adapt representations of users information
needs, commonly known as profiles.
As the result of collaborative research with Friends of
the Earth, an environmental issues campaigning
organisation, we have developed a general purpose
information classification agent architecture and have
applied it to the problem of document classification
and routing. Collaboration with Friends of the Earth
allows us to test our ideas in a non-academic context
involving high volumes of documents.
We use the technique of genetic programming (GP), (Koza
and Rice 1992), to evolve classifying agents. This is a
novel approach for document classification, where each
agent evolves a parse-tree representation of a user's
particular information need. The other unusual feature
of our research is the longevity of our agents and the
fact that they undergo a continual training process;
feedback from the user enables the agent to adapt to
the user's long-term information requirements.