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
Electronic services security management for the public administration
The public administration in Poland is constantly extending and improving electronic services provided to citizens, business and itself (e.g. one ministry providing services to another public administration institution)....
Visual analysis techniques for medical diagnosis support
A brief overview of basic inference attacks and protection controls for statistical databases
With cyber-attacks on the dramatic rise in the recent years, the number of entities which realize the necessity of protecting their IT assets increases. Individuals are more aware of the potential threats and demand high...
Concept of interoperability of clinical carepaths and the electronic health record systems conditions implementation
In contents of paper a description of requirements to the manner of the implementation of the nonvisual interface to systems of the type EHR (electronic health record) was described. That all was carried out as part of...
Web services hybrid composition, grouping and execution platform
The paper describes a software platform that implements the concept of hybrid composition, grounding and execution. The described platform allows to use different methods to build, ground and execute service composition...