POS-HOML: POS Tagging Technique For Gujarati Language Using Hybrid Optimal And Machine Learning Approaches

POS-HOML: POS Tagging Technique For Gujarati Language Using Hybrid Optimal And Machine Learning Approaches
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© 2021 by IJETT Journal
Volume-69 Issue-11
Year of Publication : 2021
Authors : Pooja M Bhatt, Dr. Amit Ganatra
DOI :  10.14445/22315381/IJETT-V69I11P232

How to Cite?

Pooja M Bhatt, Dr. Amit Ganatra, "POS-HOML: POS Tagging Technique For Gujarati Language Using Hybrid Optimal And Machine Learning Approaches," International Journal of Engineering Trends and Technology, vol. 69, no. 11, pp. 256-262, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I11P232

Abstract
Natural language processing facilitates the interaction between humans and machines. The primary use of the POS is to recognize words` tags, such as nouns, verbs, and adjectives. For the Indian language, it is a difficult task to allocate the correct POS tag to each word in a judgment because of some unknown words in Indian languages. The earlier work for Indian languages was dependent on statistical and rule-based approaches. The Statistical approaches used mathematical equations, while the rule-based approach needs precise language knowledge and hand-written rule. This paper suggests the POS category method for Gujarati language using hybrid optimal and machine learning techniques (POS-HOML) to improve POS tagging. The first contribution of the proposed POS-HOML is to introduce optimal feature selection, which optimizes the multiple features to avoid dimensionality problems. The second contribution is applying the various machine learning techniques, like hidden Markov model (HMM), rule-based approach, Hybrid (combination of rule and Hidden Markov model), Recurrent neural network (RNN), Conditional random field (CRF), Long Short-Term Memory (LSTM) to classify the POS of the given text. Finally, the paper compares various methods using standard bench datasets to analyze the effectiveness of other POS methods in terms of accuracy, precession, recall, F-measure.

Keywords
POS tagging, Gujarati language, optimal, machine learning, hidden Markov model, rule-based network, Long Short-Term Memory, deep neural network

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