SMRŽ, Pavel and Petr SOJKA. Word Hy-phen-a-tion by Neural Networks. 1996. FIMU-RS-96-04.
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Basic information
Original name Word Hy-phen-a-tion by Neural Networks
Authors SMRŽ, Pavel (203 Czech Republic) and Petr SOJKA (203 Czech Republic, guarantor).
Edition FIMU-RS-96-04, 1996.
Other information
Original language English
Type of outcome Audiovisual works
Field of Study 20200 2.2 Electrical engineering, Electronic engineering, Information engineering
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
WWW Abstract PostScript PDF
RIV identification code RIV/00216224:14330/96:00030432
Organization unit Faculty of Informatics
Keywords in English neural networks;hyphenation
Tags hyphenation, neural networks
Changed by Changed by: doc. RNDr. Petr Sojka, Ph.D., učo 2378. Changed: 19/10/2006 02:23.
Abstract
We are discussing our experiments we made when learning feedforward neural network to find possible hyphenation points in all words of given language. Neural networks show to be a good device for solving this difficult problem. The structure of the multilayer neural network used is given, together with a discussion about training sets, influence of input coding and results of experiments done for the Czech language. We end up with pros and cons of our approach tested - hybrid architecture suitable for a multilingual system.
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