Interactive Text Generation for Information Retrieval

Luis Rodríguez, Alejandro Revuelta, Ismael García-Varea, Enrique Vidal

2010

Abstract

Interactive text generation is aimed at facilitating text generation in those situations where text typing is somehow constrained. This approach achieves a significant amount of typing effort reduction in most tasks. Natural language based interfaces for information retrieval constitute a good scenario to include this kind of assistance in order to improve the system usability and provide considerable help in constrained input-interfaces. An initial proposal is presented here along with an experimental framework to assess its appropriateness.

References

  1. S. Bickel and P. Haider T. Scheffer. Predicting sentences using n-gram language models. In HLT 7805: Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, pages 193-200, Morristown, NJ, USA, October 2005. Association for Computational Linguistics.
  2. P. F. Brown, J. Cocke, S. A. Della Pietra, V. J. Della Pietra, F. Jelinek, J. D. Lafferty, R. L. Mercer, and P. S. Roosin. A statistical approach to machine translation. Computational Linguistics, 16(2):79-85, 1990.
  3. F. Jelinek. Statistical Methods for Speech Recognition. The MIT Press, Cambridge, Massachusetts, USA, 1998.
  4. P. Koehn, H. Hoang, A. Birch, C. Callison-Burch, M. Federico, N. Bertoldi, B. Cowan, W. Shen, C. Moran, R. Zens, C. Dyer, O. Bojar, A. Constantin, and E. Herbst. Moses: Open source toolkit for statistical machine translation. In Annual Meeting of the Association for Computational Linguistics, June 2007.
  5. P. Koehn, F. J. Och, and D. Marcu. Statistical phrase-based translation. In Proceedings of the Human Language Technology and North American Association for Computational Linguistics Conference (HLT/NAACL), pages 48-54, Edmonton, Canada, May 2003.
  6. J. Oncina. Optimum algorithm to minimize human interactions in sequential computer assisted pattern recognition. Pattern Recognition Letters, 30(5):558-563, April 2009.
  7. Duda R, P.E. Hart, and D.G. Stork. Pattern Classification. John Wiley and Sons, New York, NY, 2nd edition, 2000.
  8. A. Revuelta-Martínez, L. Rodríguez, and I. García-Varea. Multilingual access to online help systems and databases. Procesamiento del Lenguaje Natural, 44, 2010.
  9. H. Trost, J. Matiasek, and M. Baroni. The language component of the fasty text prediction system. Applied Artificial Intelligence, 19(8):743-781, September 2005.
  10. E. Vidal, L. Rodríguez, F. Casacuberta, and I. García-Varea. Interactive pattern recognition. In Proceedings of the 4th Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms, Volume 4892 of LNCS, pages 60-71, Brno, Czech Republic, 28-30 June 2007.
  11. E. Vidal, F. Thollard, C. de la Higuera, F. Casacuberta, and R. Carrasco. Probabilistic finitestate machines - part II. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(7):1025-1039, 2005.
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Paper Citation


in Bibtex Style

@conference{pris10,
author={Luis Rodríguez and Alejandro Revuelta and Ismael García-Varea and Enrique Vidal},
title={Interactive Text Generation for Information Retrieval},
booktitle={Proceedings of the 10th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2010)},
year={2010},
pages={62-71},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003026900620071},
isbn={978-989-8425-14-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2010)
TI - Interactive Text Generation for Information Retrieval
SN - 978-989-8425-14-0
AU - Rodríguez L.
AU - Revuelta A.
AU - García-Varea I.
AU - Vidal E.
PY - 2010
SP - 62
EP - 71
DO - 10.5220/0003026900620071


in Harvard Style

Rodríguez L., Revuelta A., García-Varea I. and Vidal E. (2010). Interactive Text Generation for Information Retrieval . In Proceedings of the 10th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2010) ISBN 978-989-8425-14-0, pages 62-71. DOI: 10.5220/0003026900620071