CLUSTERING-BASED PARAMETERS FOR DETECTION OF KEYWORDS IN NATURAL TEXTS WITH CORRECTIONS ON RANDOM TEXTS

Authors

  • Oleh Kushnir Ivan Franko National University of Lviv
  • Vasyl Vasiuta Ivan Franko National University of Lviv
  • Bohdan Horon Ivan Franko National University of Lviv
  • Ivan Dovhan Ivan Franko National University of Lviv

Keywords:

computer lunguistics, keyword detection, artificial intelligence, clasteri, clustering

Abstract

Clustering-based methods are efficient in detection of keywords in natural texts. Here we present a technique for correcting the appropriate word-relevance parameters with the data obtained for random texts and simulate the dependences of those parameters on the absolute and relative word-token frequencies.

References

M. Ortuño, P. Carpena, P. Bernaola-Galván, E. Muñoz, A. M. Somoza, Europhys. Lett., 57, 759 (2002).

J. P. Herrera, P. A. Pury, Eur. Phys. J. B, 63, 135 (2008).

H. Zhou, G. W. Slater, Physica A, 329, 309 (2003).

P. Carpena, P. Bernaola-Galván, M. Hackenberg, A. V. Coronado, J. L. Oliver, Phys. Rev. E, 79, 035102(R) (2009).

P. Carpena, P. A. Bernaola-Galván, C. Carretero-Campos, A. V. Coronado, Phys. Rev. E, 94, 052302 (2016).

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Published

2025-06-03

Conference Proceedings Volume

2025: 2nd International Scientific and Practical Conference "Problems of Computer Science, Software Modeling and Security of Digital Systems"

Section

Computer science.