Abstract
New developments in Information Technology and an ever-growing amount of unstructured business text documents in digital form require intelligent tools for precisely determining their content and relevance. In this paper we give an overview of the natural language processing approach to information extraction and information retrieval. Our article contains a brief description of efficient linguistic core components.
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References
Abney S. Partial parsing via finite-state cascades, In: Proceedings of the ESSLLI 96 Robust Parsing Workshop, 1996
Abramowicz W., Piskorski J., Gewinnen von Informationen aus aktiven und passiven Informationsquellen im Internet. International Conference on Business Information Systems, Poznan 1997
Bikel D., Miller S., Schwartz R., Weischedel R. Nymble: a High-Performance Learning name-finder
Brants T. Tagging and parsing with cascaded Markov models — Automation of corpus annotation. Doctoral dissertation, University of Saarland, Saarbrucken, 1999, http://www.dfki.de/lt/diss
Charniak E. Statistical Language Learning. MIT — Press, 1993
Cole R.A., Mariani J., Uszkoreit H., Zaenen A., Zue V. Survey of the State of the Art in Human Language Technology, Cambridge University Press ISBN 0-521-59277-1
Grishman R. Information Extraction Techniques and Challenges, Lecture Notes in Artificial Intelligence 1299, Pazienza M.T. (ed) — Information Exrtraction, 1997
Grishman R., Sundheim B. Message Understanding Conference — 6: A Brief History. In: Proceedings of the 16th International Conference on Computational Linguistics (COLING), Kopenhagen, Denmark, 1996, pp 466 – 471
Mohri M . Finite-state transducers in language and speech processing. Computational Linguistics 23, 1997
L. Shiuan Peh, Christopher Hian Ann Ting. A divide-and-conquer strategy for parsing. In: Proceedings of the ACL/SIGPARSE 5th International Workshop on Parsing Technologies, 1996, pp 57–66
Piskorski J., Neumann G. An Intelligent Text Extraction and Navigation System. To appear in the Proceedings of RIAO 2000 — Content-Based multimedia Information Access, Paris, France, 2000
Pollard C., Sag I.A. Information-Based Syntax and Semantics, vol 1, Fundamentals. No. 13 in CSLI Lecture Notes, Stanford CSLI Publications
Roche E., Schabes Y. Deterministic part-of-speech tagging with finite state transducers. Comnputational Linguistics, 21 (2): 227 – 253, 1995
Roche E., Schabes Y. Introduction to finite-state devices in natural language processing. Technical report, Mitsubishi Electric Research Laboratories, TR-96-13, 1996
SAIC, editor, Seventh Message Understanding Conference (MUC-7), http://www.muc.saic.com, 1998
Skut W., Krenn B., Brants T., Uszkoreit H. An Annotation Scheme for Free Word Order Languages. In: Proceedings of ANLP 1997, Washington D.C., 1997
Wauschkuhn O., Ein werkzeug zur partiellen syntaktischen analyse deutscher textkor- pora, In: Gibbon D. (ed) Natural Language Processing and Speech Technology. Results of the Third KONVENS Conference, Mouton de Gruyter, Berlin, 1996, pp 356 – 368
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Piskorski, J., Skut, W. (2000). Intelligent Information Extraction. In: Abramowicz, W., Orlowska, M.E. (eds) BIS 2000. Springer, London. https://doi.org/10.1007/978-1-4471-0761-3_13
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DOI: https://doi.org/10.1007/978-1-4471-0761-3_13
Publisher Name: Springer, London
Print ISBN: 978-1-85233-282-2
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