A Combined Approach to Part-of-Speech Tagging Using Features Extraction and Hidden Markov Model
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 2
Abstract
Words are characterized by its features. In an inflectional language, category of a word can be express by its tense, aspect and modality (TAM). Extracting features from an inflected word, one can categorised it with proper morphology. Hence features extraction could be a technique of part-of-speech (POS) tagging for morphologically inflected languages. Again, many words could have same features with distinguish meaning in context. However contextual meaning could be recovered using Hidden Markov Model (HMM). In this paper we try to find out a common solution for part-of-speech tagging of English text using both approaches. Here we attempt to tag words with two perspectives: one is feature analysis where the morphological characteristics of the word are analyse and second is HMM to measure the maximum probability of tag based on contextual meaning with previous tag. Words are characterized by its features. In an inflectional language, category of a word can be express by its tense, aspect and modality (TAM). Extracting features from an inflected word, one can categorised it with proper morphology. Hence features extraction could be a technique of part-of-speech (POS) tagging for morphologically inflected languages. Again, many words could have same features with distinguish meaning in context. However contextual meaning could be recovered using Hidden Markov Model (HMM). In this paper we try to find out a common solution for part-of-speech tagging of English text using both approaches. Here we attempt to tag words with two perspectives: one is feature analysis where the morphological characteristics of the word are analyse and second is HMM to measure the maximum probability of tag based on contextual meaning with previous tag.
Authors and Affiliations
Bhairab Sarma , Prajadhip Sinha , Dr. Bipul Shyam Purkayastha
Keywords
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