Abstract
We propose a method for semi-automatic construction of an ontology of a given branch of science for measuring its evolution in time. The method relies on a collection of documents in the given thematic domain. We observe that the words of different levels of abstraction are located within different parts of a document: say, the title or abstract contains more general words than the body of the paper. What is more, the hierarchical structure of the documents allows us to determine the parent-child relation between words: e.g., a word that appears in the title of a paper is a candidate for a parent of the words appearing in the body of this paper; if such a relation is repeated several times, we register such a parent-child pair in our ontology. Using the papers corresponding to different years, we construct such an ontology for each year independently. Comparing such ontologies (using tree edit distance measure) for different years reveals the trends of evolution of the given branch of science.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kuhn, T.S.: The Structure of Scientific Revolutions, 2nd edn. University of Chicago Press (1970)
References Book of Proceedings of Free Economic Society of Russia. (1983–2000), Vol.4. p. 756, Moscow, Russia (2000)
Makagonov, P., Alexandrov, P.M., Sboychakov, K.: A toolkit for development of the domain-oriented dictionaries for structuring document flows. In: Kiers, H.A., et al. (eds.) Data Analysis, Classification, and Related Methods, Studies in classification, data analysis, and knowledge organization, pp. 83–88. Springer, Heidelberg (2000)
IRBIS Automated Library System, Russian National Public Library for Science and Technology, http://www.gpntb.ru
Gelbukh, A., Alexandrov, M., Han, S.-Y.: Detecting Inflection Patterns in Natural Language by Minimization of Morphological Model. In: Sanfeliu, A., Martínez Trinidad, J.F., Carrasco Ochoa, J.A. (eds.) CIARP 2004. LNCS, vol. 3287, pp. 432–438. Springer, Heidelberg (2004)
Wagner III, J.A., Gooding, R.Z.: Effects of Societal Trends on Participation Research. Administrative Science Quarterly 32, 241–262 (1987)
Makagonov, P., Ruiz Figueroa, A., Sboychakov, K., Gelbukh, A.: Learning a Domain Ontology from Hierarchically Structured Texts. In: Proc. of Workshop Learning and Extending Lexical Ontologies by using Machine Learning Methods at 22nd International Conference on Machine Learning, ICML 2005, Bonn, Germany (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Makagonov, P., Figueroa, A.R., Gelbukh, A. (2006). Studying Evolution of a Branch of Knowledge by Constructing and Analyzing Its Ontology. In: Kop, C., Fliedl, G., Mayr, H.C., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2006. Lecture Notes in Computer Science, vol 3999. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11765448_4
Download citation
DOI: https://doi.org/10.1007/11765448_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34616-6
Online ISBN: 978-3-540-34617-3
eBook Packages: Computer ScienceComputer Science (R0)