Split-Based Algorithm for Weighted Context-Free Grammar Induction

Split-Based Algorithm for Weighted Context-Free Grammar Induction

The split-based method in a weighted context-free grammar (WCFG) induction was formalised and verified on a comprehensive set of context-free languages. WCFG is learned using a novel grammatical inference method. The proposed method learns WCFG from both positive and negative samples, whereas the we...

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Main Authors: Mateusz Gabor, Wojciech Wieczorek, Olgierd Unold
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Applied Sciences
Subjects:
grammar inference
weighted context-free grammar
split algorithm
unsupervised learning
Online Access:https://www.mdpi.com/2076-3417/11/3/1030
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spelling doaj-2b2f93f2f0ca421b9729935826e160d42021-01-25T00:00:23ZengMDPI AGApplied Sciences2076-34172021-01-01111030103010.3390/app11031030Split-Based Algorithm for Weighted Context-Free Grammar InductionMateusz Gabor0Wojciech Wieczorek1Olgierd Unold2Department of Field Theory, Electronic Circuits and Optoelectronics, Wroclaw University of Science and Technology, 50-370 Wroclaw, PolandDepartment of Computer Science and Automatics, University of Bielsko-Biala, 43-309 Bielsko-Biala, PolandDepartment of Computer Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, PolandThe split-based method in a weighted context-free grammar (WCFG) induction was formalised and verified on a comprehensive set of context-free languages. WCFG is learned using a novel grammatical inference method. The proposed method learns WCFG from both positive and negative samples, whereas the weights of rules are estimated using a novel Inside–Outside Contrastive Estimation algorithm. The results showed that our approach outperforms in terms of F1 scores of other state-of-the-art methods.https://www.mdpi.com/2076-3417/11/3/1030grammar inferenceweighted context-free grammarsplit algorithmunsupervised learning
collection DOAJ
language English
format Article
sources DOAJ
author Mateusz Gabor
Wojciech Wieczorek
Olgierd Unold
spellingShingle Mateusz Gabor
Wojciech Wieczorek
Olgierd Unold
Split-Based Algorithm for Weighted Context-Free Grammar Induction
Applied Sciences
grammar inference
weighted context-free grammar
split algorithm
unsupervised learning
author_facet Mateusz Gabor
Wojciech Wieczorek
Olgierd Unold
author_sort Mateusz Gabor
title Split-Based Algorithm for Weighted Context-Free Grammar Induction
title_short Split-Based Algorithm for Weighted Context-Free Grammar Induction
title_full Split-Based Algorithm for Weighted Context-Free Grammar Induction
title_fullStr Split-Based Algorithm for Weighted Context-Free Grammar Induction
title_full_unstemmed Split-Based Algorithm for Weighted Context-Free Grammar Induction
title_sort split-based algorithm for weighted context-free grammar induction
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2021-01-01
description The split-based method in a weighted context-free grammar (WCFG) induction was formalised and verified on a comprehensive set of context-free languages. WCFG is learned using a novel grammatical inference method. The proposed method learns WCFG from both positive and negative samples, whereas the weights of rules are estimated using a novel Inside–Outside Contrastive Estimation algorithm. The results showed that our approach outperforms in terms of F1 scores of other state-of-the-art methods.
topic grammar inference
weighted context-free grammar
split algorithm
unsupervised learning
url https://www.mdpi.com/2076-3417/11/3/1030
work_keys_str_mv AT mateuszgabor splitbasedalgorithmforweightedcontextfreegrammarinduction
AT wojciechwieczorek splitbasedalgorithmforweightedcontextfreegrammarinduction
AT olgierdunold splitbasedalgorithmforweightedcontextfreegrammarinduction
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