Machine learning text classification model with NLP approach

Simple item page
dc.citation.epage73
dc.citation.journalTitleComputational Linguistics and Intelligent Systems
dc.citation.spage71
dc.citation.volume2 : Proceedings of the 3nd International conference, COLINS 2019. Workshop, Kharkiv, Ukraine, April 18-19, 2019
dc.contributor.affiliationNational Technical University "Kharkiv Polytechnic Institute"
dc.contributor.authorRazno, Maria
dc.coverage.placenameLviv
dc.date.accessioned2019-10-31T13:21:02Z
dc.date.available2019-10-31T13:21:02Z
dc.date.created2019-04-18
dc.date.issued2019-04-18
dc.description.abstractThis article describes the relevance of the word processing task that is written in human language by the methods of Machine Learning and NLP approach, that can be used on Python programming language. It also portrays the concept of Machine Learning, its main varieties and the most popular Pythonpackages and libraries for working with text data using Machine Learning methods. The concept of NLP and the most popular python packages are also presented in the article. The machine learning classification model algorithm based on the text processing is introduced in the article. It shows how to use classification machine learning and NLP methods in practice.
dc.format.extent71-73
dc.format.pages3
dc.identifier.citationRazno M. Machine learning text classification model with NLP approach / Maria Razno // Computational Linguistics and Intelligent Systems. — Lviv : Lviv Politechnic Publishing House, 2019. — Vol 2 : Proceedings of the 3nd International conference, COLINS 2019. Workshop, Kharkiv, Ukraine, April 18-19, 2019. — P. 71–73. — (Student section).
dc.identifier.citationenRazno M. Machine learning text classification model with NLP approach / Maria Razno // Computational Linguistics and Intelligent Systems. — Lviv Politechnic Publishing House, 2019. — Vol 2 : Proceedings of the 3nd International conference, COLINS 2019. Workshop, Kharkiv, Ukraine, April 18-19, 2019. — P. 71–73. — (Student section).
dc.identifier.issn2523-4013
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/45487
dc.language.isoen
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofComputational Linguistics and Intelligent Systems (2), 2019
dc.relation.referencesen1. Langley, P.: Human and machine learning.Machine Learning,1, pp. 243–248 (1986)
dc.relation.referencesen2. Masch, C.: Text classification with Convolution Neural Net-works on Yelp, IMDB & sentence polarity dataset, https://github.com/cmasch/cnn-text-classification,24/02/2019.
dc.relation.referencesen3. Moschitti, A., Basili, R.: Complex Linguistic Features for Text Classification: A Comprehensive Study. In: Lecture Notes in Computer Science vol. 2997, pp. 181-196, Springer Science + Business Media (2004)
dc.relation.urihttps://github.com/cmasch/cnn-text-classification,24/02/2019
dc.rights.holder© 2019 for the individual papers by the papers’ authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.
dc.subjectMachine learning
dc.subjectPython
dc.subjectPandas
dc.subjectText classification
dc.subjectNLP
dc.subjectNLTK
dc.subjectScikit-learn
dc.subjectArtificial Intelligence
dc.subjectPython Library
dc.subjectDeep Learning Texts
dc.titleMachine learning text classification model with NLP approach
dc.typeArticle

Files

Original bundle

Now showing 1 - 2 of 2
Thumbnail Image
Name:
2019v2___Proceedings_of_the_3nd_International_conference_COLINS_2019_Workshop_Kharkiv_Ukraine_April_18-19_2019_Razno_M-Machine_learning_text_classification_71-73.pdf
Size:
410.08 KB
Format:
Adobe Portable Document Format
Download
Thumbnail Image
Name:
2019v2___Proceedings_of_the_3nd_International_conference_COLINS_2019_Workshop_Kharkiv_Ukraine_April_18-19_2019_Razno_M-Machine_learning_text_classification_71-73__COVER.png
Size:
293.21 KB
Format:
Portable Network Graphics
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.94 KB
Format:
Plain Text
Description:
Download

Collections

Computational linguistics and intelligent systems. – 2019 р.