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dc.contributor.authorMutwiri, George
dc.contributor.authorMutua, Makau
dc.contributor.authorOmamo, Amos
dc.date.accessioned2022-08-30T12:52:11Z
dc.date.available2022-08-30T12:52:11Z
dc.date.issued2022-06
dc.identifier.citationMutwiri, G. et al,. (2022, June 28-30). A review of techniques for morphological analysis in natural language processing. [Paper Presentation].The Inaugural Meru University of Science and Technology International Conference, Meru.en_US
dc.identifier.urihttp://repository.must.ac.ke/handle/123456789/764
dc.description.abstractNatural language is a crucial tool to facilitate communication in our day-to-day activities. This can be achieved either in text or speech forms. Natural language processing (NLP) involves making computers understand and process natural language. NLP has enhanced the way humans interact with computers, from having computers use speech to talk to humans as well as having computers translate human speech. Apart from speech, computers also create and understand sentences in natural language in a process called morphological analysis. Morphological analysis is an important part in natural language processing, being applied as a preprocessing step in most NLP tasks. Morphological analysis consists of four subtasks, that is, lemmatization, part-of-speech (POS) tagging, word segmentation and stemming. In this paper, we explore in detail each of these tasks of morphological analysis. We then evaluate the techniques used in this NLP field. Finally, we give a summary of the results of each of these techniques.en_US
dc.language.isoenen_US
dc.publisherMeru University of Science and Technologyen_US
dc.subjectNatural Language Processing (NLP)en_US
dc.subjectMorphological segmentationen_US
dc.subjectLow resource languageen_US
dc.subjectLemmatizationen_US
dc.subjectSpeech taggingen_US
dc.titleA review of techniques for morphological analysis in natural language processingen_US
dc.typeArticleen_US


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