- author = "Chris Clack and Jonny Farringdon and Peter Lidwell and Tina Yu",
- title = "Autonomous Document Classification for Business",
- institution = "University College London",
- year = "1996",
- type = "Research Note",
- number = "RN/96/48",
- address = "Computer Science, Gower Street, London, WC1E 6BT, UK",
- month = jun,
- note = "Appears in Autonomous Agents '97",
- keywords = "genetic algorithms, genetic programming, Softbot, agent architecture, pattern recognition, long term adaptation and learning",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/clack_1997_adcb.pdf",
-
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.",
- notes = "see also \cite{clack:1997:adcb}",
- size = "8 pages",
