Related papers: Hidden Markov Based Mathematical Model dedicated to Extract Ingredients from Recipe Text

Hidden Markov Based Mathematical Model dedicated to Extract Ingredients from Recipe Text

URL: http://arxiv.org/abs/2110.15707v1
Date: Tue, 28 Sep 2021 14:38:11 GMT
Title: Hidden Markov Based Mathematical Model dedicated to Extract Ingredients from Recipe Text
Authors: Zied Baklouti (UP, ENIT)
Abstract summary: Partof-speech tagging (POS tagging) is a pre-processing task that requires an annotated corpus. I performed a mathematical model based on Hidden Markov structures and obtained a high-level accuracy of ingredients extracted from text recipe.
Score: 0.0
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Natural Language Processing (NLP) is a branch of artificial intelligence that gives machines the ability to decode human languages. Partof-speech tagging (POS tagging) is a pre-processing task that requires an annotated corpus. Rule-based and stochastic methods showed remarkable results for POS tag prediction. On this work, I performed a mathematical model based on Hidden Markov structures and I obtained a high-level accuracy of ingredients extracted from text recipe with performances greater than what traditional methods could make without unknown words consideration.

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