Detailed Information on Publication Record
2003
Searching for Significant Word Associations in Text Documents Using Genetic Algorithms
ŽIŽKA, Jan, Michal ŠRÉDL and Aleš BOUREKBasic information
Original name
Searching for Significant Word Associations in Text Documents Using Genetic Algorithms
Authors
ŽIŽKA, Jan (203 Czech Republic, guarantor), Michal ŠRÉDL (203 Czech Republic) and Aleš BOUREK (203 Czech Republic)
Edition
Berlin Heidelberg New York, Computional Linguistics and Intelligent Text Processing, p. 584-587, 4 pp. 2003
Publisher
Springer Verlag
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Mexico
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/00216224:14330/03:00009148
Organization unit
Faculty of Informatics
ISBN
3-540-00532-3
UT WoS
000182492300064
Keywords in English
machine learning; text document processing; genetic algorithms; naive Bayes method
Změněno: 8/9/2004 16:37, doc. Ing. Jan Žižka, CSc.
Abstract
V originále
The paper describes experiments that used Genetic Algorithms for looking for important word assocoations (phrases) in unstructured text documents obtained from the Internet in the area of a specialized medicine branch. Genetic alforithms can evolve sets of word associations with assigned significance weights from the document categorization point of view (relevant and irrelevant documents). The categorization is similarly reliable like the naive Bayes classification based on individual words. In addition, genetic algorithms provided phrases consisting of one, two, and three words. The phrases were quite meaningful from the human point of view.
Links
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