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Erschienen in:
On Fuzzy RDM-Arithmetic Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Hidden Markov Models with Affix Based Observation in the Field of Syntactic Analysis

verfasst von : Marcin Pietras

Erschienen in: Hard and Soft Computing for Artificial Intelligence, Multimedia and Security

Verlag: Springer International Publishing

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Abstract

This paper introduces Hidden Markov Models with N-gram observation based on words bound morphemes (affixes) used in natural language text processing focusing on the field of syntactic classification. In general, presented curtailment of the consecutive gram’s affixes, decreases the accuracy in observation, but reveals statistically significant dependencies. Hence, considerably smaller size of the training data set is required. Therefore, the impact of affix observation on the knowledge generalization and associated with this improved word mapping is also described. The focal point of this paper is the evaluation of the HMM in the field of syntactic analysis for English and Polish language based on Penn and Składnica treebank. In total, a 10 HMM differing in the structure of observation has been compared. The experimental results show the advantages of particular configuration.

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Vorheriges Kapitel On Fuzzy RDM-Arithmetic
Nächstes Kapitel Opinion Acquisition: An Experiment on Numeric, Linguistic and Color Coded Rating Scale Comparison
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Metadaten
Titel
Hidden Markov Models with Affix Based Observation in the Field of Syntactic Analysis
verfasst von
Marcin Pietras
Copyright-Jahr
2017
Buch
Hard and Soft Computing for Artificial Intelligence, Multimedia and Security

Print ISBN: 978-3-319-48428-0

Electronic ISBN: 978-3-319-48429-7

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-48429-7_2

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