Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-03T01:35:21.644Z Has data issue: false hasContentIssue false
  • English
  • Français

Discourse planning for information composition and delivery: A reusable platform

Published online by Cambridge University Press:  15 December 2009

CÉCILE PARIS ,
NATHALIE COLINEAU ,
ANDREW LAMPERT  and
KEITH VANDER LINDEN
CÉCILE PARIS
Affiliation:
CSIRO – ICT Centre, PO Box 76, Epping, NSW 1710, Australia e-mails: [email protected], [email protected], [email protected]
NATHALIE COLINEAU
Affiliation:
CSIRO – ICT Centre, PO Box 76, Epping, NSW 1710, Australia e-mails: [email protected], [email protected], [email protected]
ANDREW LAMPERT
Affiliation:
CSIRO – ICT Centre, PO Box 76, Epping, NSW 1710, Australia e-mails: [email protected], [email protected], [email protected]
KEITH VANDER LINDEN
Affiliation:
Department of Computer Science, Calvin College, Grand Rapids, MI 49546, USA e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

To work effectively in information-rich environments, knowledge workers must be able to distil the most appropriate information from the deluge of information available to them. This is difficult to do manually. Natural language engineers can support these workers by developing information delivery tools, but because of the wide variety of contexts in which information is acquired and delivered, these tools have tended to be domain-specific, ad hoc solutions that are hard to generalise. This paper discusses Myriad, a platform that generalises the integration of sets of resources to a variety of information delivery contexts. Myriad provides resources from natural language generation for discourse planning as well as a service-based architecture for data access. The nature of Myriad's resources is driven by engineering concerns. It focuses on resources that reason about and generate from coarse-grained units of information, likely to be provided by existing information sources, and it supports the integration of pipe-lined planning and template mechanisms. The platform is illustrated in the context of three information delivery applications and is evaluated with respect to its utility.

Type
Papers
Information
Natural Language Engineering , Volume 16 , Issue 1 , January 2010 , pp. 61 - 98
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Androutsopoulos, I., Oberlander, J., and Karkaletsis, V. 2007. Source authoring for multilingual generation of personalised object descriptions. Natural Language Engineering 13 (3): 191–233, Cambridge University Press. Published Online by Cambridge University Press 19 Jun 2006.CrossRefGoogle Scholar
Appelt, D. 1985. Planning English Sentences. Cambridge, England, UK: Cambridge University Press.CrossRefGoogle Scholar
Austin, J. 1962. How to Do Things with Words. England, UK: Oxford University Press.Google Scholar
Balbo, S., Ozkan, N., and Paris, C. 2004. Choosing the right task-modeling notation: a taxonomy. In Prof.Diaper, Dan, and Prof.Stanton, Neville (eds.), The Handbook of Task Analysis for Human-Computer Interaction, pp. 445–465. Mahwah, New Jersey and London: Lawrence Erlbaum Associates.Google Scholar
Bateman, J. A. 1997. Enabling technology for multilingual natural language generation: the KPML development environment. Natural Language Engineering 3 (1): 15–55.CrossRefGoogle Scholar
Bateman, J. A., Kamps, T., Kleinz, J., and Reichenberger, K. 2001. Constructive text, diagram and lay-out generation for information presentation. Computational Linguistics 27 (3): 409–449.CrossRefGoogle Scholar
Boyle, C., and Encarnacion, A.O. 1994. MetaDoc: an adaptive hypertext reading system. User Modeling and User-Adapted Interaction 4 (1): 1–19.CrossRefGoogle Scholar
Brachman, R. J., and Schmolze, J. 1985. An overview of the KL-ONE knowledge representation system. Cognitive Science 9: 171–216.Google Scholar
Brusilovsky, P., Karagiannidis, C., and Sampson, D. 2004. Layered evaluation of adaptive learning systems. International Journal of Continuing Engineering Education and Lifelong Learning 14 (4/5): 402–421.CrossRefGoogle Scholar
Chen, J., Bangalore, S., Rambow, O., and Walker, M. 2002. Towards automatic generation of natural language generation systems. In the Proceedings of the International Conference on Computational Linguistics (COLING 2002), pp. 1–7, Taipei, Taiwan.Google Scholar
Colineau, N., Lampert, A., and Paris, C. 2004a. Task-sensitive user interfaces: grounding information provision within the context of the user's activity. In Proceedings of the International Conference on Advanced Visual Interfaces (AVI'04), pp. 218–225, Gallipoli, Italy.Google Scholar
Colineau, N., and Paris, C. 2003. Task-driven information presentation. In Proceedings of the Annual Conference of the Computer-Human Interaction (OZCHI'03), pp. 138–146, Special Interest Group of the Ergonomics Society of Australia, Brisbane, Australia.Google Scholar
Colineau, N., and Paris, C. 2006. Towards assessing the affordability of an adaptive hypermedia system. Technical Report TR06/021, CSIRO – ICT Centre.CrossRefGoogle Scholar
Colineau, N., and Paris, C. 2007. Tailoring and the Efficiency of information seeking. In Proceedings of the 11th International Conference on User Modelling (UM 2007), pp. 440–444, Corfu, Greece.Google Scholar
Colineau, N., Paris, C. and Wu, M. 2004b. Actionable information delivery. Revue d'Intelligence Artificielle (RSTI – RIA), Special Issue on Tailored Information Delivery 18 (4): 549–576.CrossRefGoogle Scholar
Colineau, N., Paris, C., and Vander Linden, K. 2002. An evaluation of procedural instructional text. In Proceedings of the International Natural Language Generation Conference (INLG), pp. 128–135, New York.Google Scholar
Colineau, N., Phalip, J., and Lampert, A. 2006. The delivery of multimedia presentations in a graphical user interface environment. In Proceedings of the 2006 International Conference on Intelligent User Interfaces (IUI'2006), pp. 279–281, Sydney, Australia.Google Scholar
Danlos, L. 1987. The linguistic basis of text generation. Cambridge, England, UK: Cambridge University Press.CrossRefGoogle Scholar
Davey, A. 1979. Discourse Production: A Computer Model of Some Aspects of a Speaker. Edinburgh, Scotland: Edinburgh University Press.Google Scholar
De Carolis, B., de Rosis, F., Berry, D., and Michas, I. 1999. Evaluating plan-based hypermedia generation. In Proceedings of the 7th European Workshop on Natural Language Generation, pp. 126–134, Toulouse, France.Google Scholar
Elhadad, M. 1988. FUF: The universal unifier – user manual. Technical Report CUCS-408–88, Department of Computer Science, Columbia University, New York.Google Scholar
Elhadad, N. McKeown, K. Kaufman, D., and Jordan, D. 2005. Facilitating physicians' access to information via tailored text summarization. In Proceedings of AMIA Annual Symposium, pp. 226–230, Washington, DC.Google Scholar
Erl, T. 2005. Service-Oriented Architecture: Concepts, Technology, and Design. Upper Saddle River, NJ: Prentice Hall PTR.Google Scholar
Gates, K. F., Lawhead, P. B., and Wilkins, D. E. 1998. Toward an adaptive WWW: a case study in customized hypermedia. New Review of Multimedia and Hypermedia 4: 89–113.CrossRefGoogle Scholar
Goldberg, E., Driedger, N., and Kittredge, R. 1994. Using natural-language processing to produce weather forecases. IEEE Expert 9 (2): 45–53.CrossRefGoogle Scholar
Green, N., Carenini, G., Kerpedjiev, S., Roth, S., and Moore, J. D. 1998. A Media-independent content language for integrated text and graphics generation. In Proceedings of the Workshop on Content Visualization and Intermedia Representations (CVIR'98) of the 36th Annual Meeting of the Association for Computational Linguistics (COLING-ACL'98), pp. 69–75. Montreal, Canada.Google Scholar
Herder, E. 2003. Utility-based evaluation of adaptive systems. In Proceedings of the 2nd Workshop on Empirical Evaluation of Adaptive Systems at the User Modeling Conference (UM'2003), pp. 25–30, Pittsburgh, PA.Google Scholar
Hothi, J., and Hall, W. 1998. An evaluation of adapted hypermedia techniques using static user modelling. In Proceedings of the 2nd Adaptive Hypertext and Hypermedia Workshop at the 9th ACM International Hypertext Conference (Hypertext'98), Pittsburgh, PA.Google Scholar
Iordanskaja, L., Myunghee, K., Kittredge, R., Lavoie, B., and Polguère, A. 1992. Generation of extended bilingual statistical reports. In Proceedings of the 15th International Conference on Computational Linguistics, pp. 1019–1023, Nantes, France.CrossRefGoogle Scholar
Joachims, T., Freitag, D., and Mitchell, T. 1997. WebWatcher: a tour guide for the World Wide Web. In Proceedings of 15th International Joint Conference on Artificial Intelligence (IJCAI), pp. 770–775, Nagoya, Aichi, Japan.Google Scholar
Johnston, M., Bangalore, S., Vasireddy, G., Stent, A., Ehlen, P., Walker, M., Whittaker, S., and Maloor, P. 2002. MATCH: an architecture for multimodal dialogue systems. In the Proceedings of the 40th Annual Meeting on Association for Computational Linguistics (ACL'02), pp. 376–383, Philadelphia, PA.Google Scholar
Kosseim, L., and Lapalme, G. 2000. Choosing rhetorical structures to plan instructional texts. Computational Intelligence 16 (3): 408–445, Boston, MA: Blackwell Publishers.CrossRefGoogle Scholar
Kushniruk, A., Kan, MY, McKeown, K., Klavans, J., Jordan, D., LaFlamme, M., and Patel, V. 2002. Usability evaluation of an experimental text summarization system and three search engines: implications for the reengineering of health care interfaces. In Proceedings of the AMIA Annual Symposium, pp. 420–424, San Antonio, TX.Google Scholar
Lampert, A., and Paris, C. 2004. Information assembly for adaptive display. In Proceedings of 2004 Australasian Language Technology Workshop (ALTW2004), pp. 63–70, Sydney, Australia.Google Scholar
Lavoie, B. Rambow, O., and Reiter, E. 1997. A fast and portable realizer for text generation. In Proceedings of the Fifth Conference on Applied Natural-Language Processing, pp. 265–268, Washington, D.C.CrossRefGoogle Scholar
Lu, S., and Paris, C. 2007. Specifying documents in an adaptive hypermedia generation environment: an authoring tool prototype. International Journal of Learning Technology, 3(3): 324–340, in Cristea, A. and Carro, R. (eds.), Special issue on Authoring of Adaptive and Adaptable Hypermedia, Geneva, Switzerland: Inderscience.Google Scholar
MacGregor, R. M. 1988. A deductive pattern matcher. In Proceedings of the seventh national conference on artificial intelligence, pp. 403–408, Saint Paul, MN.Google Scholar
Mann, W. C., and Thompson, S. A. 1988. Rhetorical structure theory: toward a functional theory of text organisation. Text 8 (3): 243–281.Google Scholar
Maybury, M. 1997. The standard reference model in the AIMI and TEXTPLAN systems. Computer Standards and Interfaces: the International Journal on the Development and Application of standards for computers, Data Communications and Interfaces 18 (6–7): 595–603.CrossRefGoogle Scholar
McDonald, D. 1980. Natural Language Production as a Process of Decision Making. PhD thesis, MIT, Cambridge, MA.Google Scholar
McKeown, K. R. 1985. Text Generation. Cambridge, England, UK: Cambridge University Press.CrossRefGoogle Scholar
Mellish, C., Scott, D., Cahill, L., Paiva, D., Evans, R., and Reape, M. 2006. A reference architecture for natural language generation systems. Natural Language Engineering 12 (1): 1–34, Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Meteer, M. 1990. The Generation Gap: The Problem of Expressability in Text Planning. PhD Thesis, Computer and Information Sciences Department, University of Massachusetts, Amherst, MA.Google Scholar
Moore, J., and Paris, C. 1993. Planning text for advisory dialogues: capturing intentional and rhetorical information. Journal of Computational Linguistics 19 (4): 651–694.Google Scholar
Moore, J., and Swartout, W. 1991. A reactive approach to explanation: taking the user's feedback into account. In Paris, C., Swartout, W., and Mann, W. (eds.) Natural-language Generation in Artificial Intelligence and Computational Linguistics, pp. 3–48. Kluwer Academic Publishers, Boston.Google Scholar
Morik, K. 1988. Discourse models, dialog memories, and user models. Computational Linguistics 14 (3): 95–97, Special Issue on User Modeling, Cambridge, MA: MIT Press.Google Scholar
Müller-Tomfelde, C., Paris, C., and Stevenson, D. 2004. Interactive landmarks: linking virtual environments with knowledge-based systems. In Proceedings of OZCHI, Wollongong, Australia.Google Scholar
Nirenburg, S., Nyberg, E., and Defrise, C. 1989. Text Planning with Opportunistic Control. Technical Report CMU-CM-T-89–113, Centre for Machine Translation, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
O'Donnell, M., Mellish, C., Oberlander, J., and Knott, A. 2001. ILEX: an architecture for a dynamic hypertext generation system. Natural Language Engineering 7 (13): 225–250, Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Ozkan, N., Balbo, S., and Paris, C. 1998. Understanding a task model: an experiment. In People and Computers XIII, pp 186–191. Sheffield, UK: Springer-Verlag.Google Scholar
Paramythis, A., Totter, A., and Stephanidis, C. 2001. A modular approach to the evaluation of adaptive user interfaces. In Proceedings of the workshop on Empirical Evaluation of Adaptive Systems at the User Modeling Conference (UM'2001), pp. 9–24, Sonthofen, Germany.Google Scholar
Paris, C. 1988. Planning a text: can we and how should we modularize this process? In Proceedings of the AAAI-1988 Workshop on Text Planning and Realization, Saint Paul, MN.Google Scholar
Paris, C. 1993. User Modelling in Text Generation. London & New York: Frances Pinter.Google Scholar
Paris, C., and Colineau, N. 2006. SciFly: tailored corporate brochures on demand. Technical Report TR06/268, CSIRO – ICT Centre.Google Scholar
Paris, C., Colineau, N., Lampert, A., and Giralt Duran, J. 2008a. Generation under space constraints. In Proceedings of the 22nd International Conference on Computational Linguistics (COLING 2008), pp. 127–129, Manchester, UK.Google Scholar
Paris, C., Colineau, N., Lampert, A., and Giralt Duran, J. 2008b. Fit it in but say it well! In Proceedings of Australasian Language Technology Workshop (ALTAW 2008), pp. 133–141, Hobart, Australia.Google Scholar
Paris, C., Colineau, N., Lu, S., and Vander Linden, K. 2005c. Automatically Generating Effective Online Help. International Journal on E-Learning 4 (1): 83–103.Google Scholar
Paris, C., Colineau, N., and Wilkinson, R. 2006. Evaluations of NLG systems: common corpus and tasks or common dimensions and metrics?. In Proceedings of the International Natural Language Generation Conference (INLG-06), held as a workshop on the COLING/ACL Conference, pp. 127–129, Sydney, Australia.Google Scholar
Paris, C., Lampert, A., Lu, S., and Wu, M. 2005a. Enhancing dynamic knowledge management services – tailored documents. Technical Report TR05/034, Commercial-in-Confidence, CSIRO ICT Centre.Google Scholar
Paris, C., Lampert, A., Lu, S., and Wu, M. 2005b. Enhancing dynamic knowledge management services – using the tailored documents environment. Technical Report TR05/036, Commercial-in-Confidence, CSIRO ICT Centre.Google Scholar
Paris, C., Lu, S., and Vander Linden, K. 2004. Environments for the construction and use of task models. In Prof.Diaper, Dan, and Prof.Stanton, Neville (eds.), The Handbook of Task Analysis for Human-Computer Interaction, pp. 467–482, Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Paris, C., Wan, S., Wilkinson, R., and Wu, M. 2001. Generating personal travel guides – and who wants them? In Bauer, M., Gmytrasiewicz, P., and Vassileva, J. (eds.) Proceedings of the International Conference on User Modelling (UM2001), pp. 251–253, Sonthofen, Germany.Google Scholar
Paris, C., Wu, M., Vercoustre, A., Wan, S., Wilkins, P., and Wilkinson, W. 2003. An empirical study of the effect of coherent and tailored document delivery as an interface to organizational websites. In Proceedings of the Adaptive Hypermedia Workshop at the User Modeling Conference (UM'03), pp. 133–144, Pittsburgh, PA.Google Scholar
Power, R., and Scott, D. 1998. Multilingual authoring using feedback texts. In Proceedings of COLING-ACL 98, pp. 1053–1059, Montreal, Canada.Google Scholar
Reiter, E. 1994. Has a consensus NL generation architecture appeared, and is it psycholinguistically plausible? In Proceedings of the Seventh International Workshop on Natural Language Generation (INLGW), pp. 163–170, Kennebunkport, ME.CrossRefGoogle Scholar
Reiter, E. 2000. Pipelines and size constraints. Computational Linguistics 26 (2): 251–259.CrossRefGoogle Scholar
Reiter, E., and Dale, R., 2000. Building Natural Language Generation Systems. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Reiter, E., Robertson, R., Lennox, A. S., and Osman, L. 2001. Using a randomised controlled clinical trial to evaluate an NLG system. In Proceedings of ACL'01, pp. 434–441, Toulouse, France.Google Scholar
Rubinoff, R. 1992. Integrating text planning and linguistic choice by annotating linguistic structures. In Dale, R., Hovy, E., Rósner, D., and Stock, O. (eds.), Aspects of Automated Natural Language Generation, pp. 45–56. Lecture Notes In Computer Science 587. Berlin: Springer Verlag.CrossRefGoogle Scholar
Sacerdoti, E. 1977. A Structure for Plans and Behavior. New York: American Elsevier North-Holland.Google Scholar
Scott, D., and de Souza, C. 2006. Getting the message across in RST-based text generation. In Dale, R., Mellish, S., and Zock, M. (eds.), Current Resarch in NLG, pp. 119–128. London: Academic Press.Google Scholar
Taboada, M., and Mann, W. 2006. Applications of rhetorical structure theory. Discourse Studies 8 (4): 567–588.CrossRefGoogle Scholar
Tarby, J. C., and Barthet, M. F. 1996. The Diane+ method. In Proceedings of the Second International Workshop on Computer-Aided Design of User Interfaces (CADUI'96), pp. 95–119, Namur, Belgium.Google Scholar
Wahlster, W., André, E., Finkler, W., Profitlich, H. J., and Rist, T. 1993. Plan-based integration of natural language and graphics generation. Artificial Intelligence 63 (1–2): 387–428.CrossRefGoogle Scholar