Hidden Markov Models as a text mining method

Journal Title: Computer Science and Mathematical Modelling - Year 2010, Vol 0, Issue 6

Abstract

In the text mining applications probabilistic models of document are widely used. In this paper the Hidden Markov Models were described as a fundamental method for text processing. Definition of the HMM was presented and the algorithms to find parameters of the model. Some of the possible applications of HMM were suggested.

Authors and Affiliations

Marcin Mazurek

Keywords

Related Articles

Ontology modeling usage for Common Operational Picture acquisition

This work concentrates mainly on methods of integrating several aspects of battlefield data using ontology models and presenting such data in rich GIS environment. Such approach allows to organize and filter data using p...

Enterprise architecture management method

In this article manner of enterprise architecture management was described. This approach encompasses software development methodology, fashion of description and tools support. Rational Unified Process (RUP) software de...

Zarządzanie ryzykiem na potrzeby infrastruktury krytycznej

W treści artykułu przedstawiono propozycję realizacji procesu zarządzania ryzykiem na potrzeby ochrony infrastruktury krytycznej jako istotnego elementu w procesie zapewnienia bezpieczeństwa państwa i jego obywateli, a t...

The method of distribution of a set of objects into multi-criteria quality clusters

The paper presents a general procedure for creating quality rankings of objects. Ranking procedure fixed set of elements by recurrent determining the extreme elements of the set on the basis of its preference relation. T...

Download PDF file
  • EP ID EP63136
  • DOI -
  • Views 119
  • Downloads 0

How To Cite

Marcin Mazurek (2010). Hidden Markov Models as a text mining method. Computer Science and Mathematical Modelling, 0(6), 27-31. https://europub.co.uk./articles/-A-63136