Abstract
Is it possible to discover semantic term relations useful for thesauri without any semantic information? Yes, it is. A recent approach for automatic thesaurus construction is based on explicit linguistic knowledge, i.e. a domain independent parser without any semantic component, and implicit linguistic knowledge contained in large amounts of real world texts. Such texts include implicitly the linguistic, especially semantic, knowledge that the authors needed for formulating their texts. This article explains how implicit semantic knowledge can be transformed to an explicit one. Evaluations of quality and performance of the approach are very encouraging.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Das-Gupta, P.: Boolean Interpretation of Conjunctions for Document Retrieval. JASIS 38(1987) 245–254
DIN 1463: Erstellung und Weiterentwicklung von Thesauri. Deutsches Institut für Normung (1987), related standard published in English: ISO 2788:1986
Grefenstette, G.: Explorations in Automatic Thesaurus Discovery. Kluwer Academic Publishers, Boston, Dordrecht, London (1994)
Güntzer, U., Jüttner, G., Seegmüller, G., Sarre, F.: Automatic Thesaurus Construction by Machine Learning from Retrieval Sessions. Inf. Proc. & Management 25(1989) 265–273
Hearst, M.: Automatic Acquisition of Hyponyms from Large Text Corpora. Proceedings of COLING 92, Nantes, Vol.2(1992) 539–545
Hindle, D.: A Parser for Text Corpora. Technical Memorandum, AT&T Bell Laboratories (1990), also published in Atkins, A., Zampolli, A.: Computational Approaches to the Lexicon. Oxford University Press (1993)
Katz, J., Fordor, J.: The Structure of Semantic Theory. In Fordor, J., Katz, J.: The Structure of Language: Readings in the Philosophy of Language. Englewood Cliffs, NJ, Prentice Hall (1964) 479–518
Lesk, M.: Word-Word Associations in Document Retrieval Systems. American Documentation (1969) 27–38
Ruge, G.: Experiments on Linguistically Based Term Associations. Inf. Proc. & Mangement 28(1992) 317–332
Ruge, G.: Wortbedeutung und Termassoziation. Reihe Sprache und Computer 14, Georg Olms Verlag, Hildesheim, Zürich, New York (1995)
Ruge, G., Schwarz, C., Warner, A.: Effectiveness and Efficiency in Natural Language Processing for Large Amounts of Text. JASIS 42(1991) 450–456
Schütze, H., Pederssn, J.: A Cooccurrence-Based Thesaurus and Two Applications to Information Retrieval. Proceedings of RIAO94, New York (1994) 266–274
Shaikevich, A.: Automatic Construction of a Thesaurus from Explanatory Dictionaries. Automatic Documentation and Mathematical Linguistics 19(1985) 76–89
Salton, G.: Automatic Term Class Construction Using Relevance — A Summary of Work in Automatic Pseudoclassification. Inf. Proc. & Management 16(1980) 1–15
Strzalkowski, T.: TTP: A Fast and Robust Parser for Natural Language. Proceedings of COLING 92, Nantes, Vol.1(1992) 198–204
Strzalkowski, T.: Natural Language Information Retrieval. Inf. Proc. & Management 31(1995) 397–417
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Ruge, G. (1997). Automatic detection of thesaurus relations for information retrieval applications. In: Freksa, C., Jantzen, M., Valk, R. (eds) Foundations of Computer Science. Lecture Notes in Computer Science, vol 1337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0052119
Download citation
DOI: https://doi.org/10.1007/BFb0052119
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63746-2
Online ISBN: 978-3-540-69640-7
eBook Packages: Springer Book Archive