Title :
Generalization analysis of the CL and MM-based classifications
Author :
Kovács, L. ; Barabás, P.
Author_Institution :
Dept. of Inf. Technol., Univ. of Miskolc, Miskolc
Abstract :
Computational linguistics covers the statistical and logical modeling of languages using computer-based software- hardware tools. An important component in CL systems is the morphological parser. The scope of our study is to build a statistical method to learn the rules of word inflection. The pre-requirement regarding the language is that the language uses words which are sequences of characters. A key factor of the required clustering algorithm is the cost efficiency. After analysis of the alternatives, two methods were selected to perform further refinement and adaptation: the observable Markov Model method and the formal concept analysis method.
Keywords :
Markov processes; computational linguistics; grammars; learning (artificial intelligence); pattern classification; pattern clustering; statistical analysis; clustering algorithm; computational linguistics; formal concept analysis; generalization analysis; logical modeling; morphological parser; observable Markov model method; pattern classification; rule learning; statistical modeling; word inflection; Clustering algorithms; Computational linguistics; Costs; Data mining; Dictionaries; Hidden Markov models; Information analysis; Information technology; Performance analysis; Statistical analysis;
Conference_Titel :
Applied Machine Intelligence and Informatics, 2008. SAMI 2008. 6th International Symposium on
Conference_Location :
Herlany
Print_ISBN :
978-1-4244-2105-3
Electronic_ISBN :
978-1-4244-2106-0
DOI :
10.1109/SAMI.2008.4469195
