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POETIC: A system for gathering and disseminating traffic information

Published online by Cambridge University Press:  12 September 2008

R. Evans
Affiliation:
Cognitive and Computing Sciences, University of Sussex, Brighton, UK
R. Gaizauskas
Affiliation:
Cognitive and Computing Sciences, University of Sussex, Brighton, UK
L. J. Cahill
Affiliation:
Cognitive and Computing Sciences, University of Sussex, Brighton, UK
J. Walker
Affiliation:
Racal Research Ltd., UK
J. Richardson
Affiliation:
Racal Research Ltd., UK
A. Dixon
Affiliation:
Racal Research Ltd., UK

Abstract

The Portable Extendable Traffic Information Collator (POETIC) is an information extraction system that extracts traffic information from free text occurring in police incident logs and initiates (simulated) broadcasts of traffic bulletins to motorists when appropriate. POETIC is a second stage prototype system; the initial prototype (TIC, see Evans and Hartley 1990) was limited to the practices and requirements of a single police force. In POETIC, the architecture and data representations have been generalised to make the system tailorable to many different police force ‘domains’. In this paper we describe these developments, and report on tests of the system on authentic input data from three police domains.

Type
Articles
Copyright
Copyright © Cambridge University Press 1995

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References

Allport, D. (1988 a) Interpreting incident reports Proceedings of the colloquium on applications of expert systems in road transportation,London:Google Scholar
Allport, D.. (1988 b) The TIC: parsing interesting text. Proceedings of the second ACL Conference on Applied Natural Language Processing, pp. 211218.CrossRefGoogle Scholar
Allport, D. (1988 c) Understanding RTA's. Proceedings of the Alvey Technical Conference.Google Scholar
Briscoe, E., Grover, C., Boguraev, B., and Carroll, J. (1987) A formalism and environment for the development of a large grammar of English. Proceedings of the 10th International Joint Conference on Artificial Intelligence, vol. 2, pp. 703708.Google Scholar
Cahill, L. J. (1992) Some reflections on the conversion of the TIC lexicon to DATR. In Default Inheritance Within Unification-based Approaches to the Lexicon, Briscoe, E., Paiva, V., and Copestake, A. (eds.). Cambridge: Cambridge University Press.Google Scholar
Cahill, L. J., and Evans, R. (1990) An application of DATR: the TIC lexicon. Proceedings of the 9th European Conference on Artificial Intelligence,Stockholm, Sweden, pp. 120125.Google Scholar
Charniak, E., and McDermott, D. (1985) Introduction to Artificial Intelligence. Reading, MA: Addison-Wesley.Google Scholar
Chinchor, N. (1991) MUC-3 evaluation metrics. Proceedings of the 3rd Message Understanding Conference (MUC-3)..CrossRefGoogle Scholar
Dixon, A., Evans, R., Walker, J., Cahill, L. J., Gaizauskas, R. and Higginson, J.. (1994) POETIC: A system for automatic detection and broadcasting of road congestion information. Towards an Intelligent Transport System – Proceedings of the 1st World Congress on Applications of Transport Telenwtics and Intelligent Vehicle-highway Systems,Paris, France, vol. 5, pp. 25472554.Google Scholar
European Broadcasting Union (1990) Guideline for the implementation of the RDS system. Technical report 3260-e.Google Scholar
Evans, R., Gaizauskas, R., and Cahill, L. J. (1993) MUCing about in Pop: message understanding in five languages! In Applications and Innovations in Expert Systems, Graham, I. M. (ed.), pp. 295308. Cambridge: BHR Group/BCS SGES.Google Scholar
Evans, R., Gaizauskas, R., and Hartley, A. (1990) POETIC – the Portable Extendable Traffic Information Collator OECD Workshop on Knowledge-based Expert Systems in Transportation, Espoo, Finland, Vol. 1, pp. 171184.Google Scholar
Evans, R., and Gazdar, G. (1989 a) Inference in DATR. Proceedings of the 4th Conference of the European Chapter of the Association for Computational Linguistics,Manchester, UK.CrossRefGoogle Scholar
Evans, R., and Gazdar, G. (1989 b) The semantics of DATR. In Proceedings of the 7th Conference of the Society for the Study of Al and Simulation of Behaviour, Cohn, A. (ed), pp. 7987. London: Pitman.Google Scholar
Evans, R., and Gazdar, G. (1996) DATR: a language for lexical knowledge representation. Computational Linguistics 22 (2).Google Scholar
Evans, R., and Hartley, A. (1990) The Traffic Information Collator. Expert Systems: The International Journal of Knowledge Engineering 7 (4): 209214.CrossRefGoogle Scholar
Gaizauskas, R. (1995) XI: A knowledge representation language based on cross-classification and inheritance. Research Memorandum CS-95-24, Department of Computer Science, University of Sheffield.Google Scholar
Gaizauskas, R., Cahill, L. J., and Evans, R. (1994) Sussex University: description of the Sussex system used for MUC-5. Proceedings of the 5th Message Understanding Conference (MUC-5),San Mateo, CA:. pp. 321335.Google Scholar
Gaizauskas, R., Wakao, T., Humphreys, K., Cunningham, H., and Wilks, Y. (1995) University of Sheffield: Description of the LaSIE system as used for MUC-6. Proceedings of the 6th Message Understanding Conference (MUC-6).San Mateo, CA:.CrossRefGoogle Scholar
Grover, C., Briscoe, E., Carroll, J., and Boguraev, B. The Alvey natural language tools grammar (second release). (1989) Technical report 162, University of Cambridge Computer Laboratory, Cambridge.Google Scholar
Hobbs, J., Stickel, M., Martin, P., and Edwards, D. (1988) Interpretation as abduction. Proceedings of the 26th Conference of the Association for Computational Linguistics,Buffalo, NY.CrossRefGoogle Scholar
Mellish, C., Allport, D., Hartley, A., Evans, E., Cahill, L. J., Gaizauskas, R., and Walker, J.. (1992) The TIC message analyser. Cognitive Science Research Paper 225,.Google Scholar
Mellish, C.. (1988) Implementing systemic classification by unification. Computational Linguistics 14 (1).Google Scholar
Palmer, M., and Finin, T. (1990) Workshop on the evaluation of natural language processing systems. Computational Linguistics 16 (3).Google Scholar
Schank, R., and Abelson, R. (1977) Scripts, Plans, Goals and Understanding. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Sundheim, B. M.. Overview of the third message understanding evaluation and conference. (1991) Proceedings of the 3rd Message Understanding Conference (MUC-3).CrossRefGoogle Scholar