Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Single Password Authentication Protocol Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Bayesian Multinomial Naïve Bayes Classifier to Text Classification

Authors : Shuo Xu, Yan Li, Zheng Wang

Published in: Advanced Multimedia and Ubiquitous Engineering

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Text classification is the task of assigning predefined classes to free-text documents, and it can provide conceptual views of document collections. The multinomial naïve Bayes (NB) classifier is one NB classifier variant, and it is often used as a baseline in text classification. However, multinomial NB classifier is not fully Bayesian. This study proposes a Bayesian version NB classifier. Finally, experimental results on 20 newsgroup show that Bayesian multinomial NB classifier with suitable Dirichlet hyper-parameters has similar performance with multinomial NB classifier.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter The LTC Framework for Competitive Analysis on Industrial Technology
next chapter CERIF: A Research Information Model for Electric Vehicles Decision Support System
Footnotes
1
20 newsgroup data can be available online from http://​mlcomp.​org/​datasets/​379.
 
Literature
1.
Aggarwal, C.C., Zhai, C.: A survey of text classification algorithms. In: Mining Text Data, pp. 163–222. Springer (2012)
2.
McCallum, A., Nigam, K.: A comparison of event models for naive Bayes text classification. In: ICML/AAAI-98 Workshop on Learning for Text categorization, AAAI, pp. 41–48 (1998)
3.
Rish, I.: An empirical study of the naïve Bayes classifier. In: IJCAI Workshop on Emprical Methods in AI (2001)
4.
Bird, S., Klein, E., Loper, E. (eds.): Natural Language Processing with Python. O’Reilly, Springfield (2009)MATH
5.
Rennie, J.D.M., Shih, L., Teevan, J., Karger, D.R.: Tackling the poor assumptions of naive bayes text classifiers. In: Proceedings of the 20th International Conference on Machine Learning (2003)
6.
Manning, C.D., Raghavan, P., Schütze, H. (eds.): Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)MATH
7.
Lang, K.: Newswenews: learning to filter netnews. In: Proceedings of the 12th International Conference on Machine Learning, pp. 331–339 (1995)
8.
Pedregosa, F., Varoquaus, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12(2), 2825–2830 (2011)MathSciNetMATH
9.
Xu, S., Ma, F., Tao, L.: Learn from the information contained in the false splice sites as well as in the true splice sites using SVM. In: Proceedings of the International Conference on Intelligent Systems and Knowledge Engineering, Amsterdam, pp. 1360–1366. Atlantis Press, Netherlands (2007)
10.
Rennie, J.D.M.: Improving multi-class text classification with naive Bayes. Master’s thesis, Massachusetts Institute of Technology (2001)
Metadata
Title
Bayesian Multinomial Naïve Bayes Classifier to Text Classification
Authors
Shuo Xu
Yan Li
Zheng Wang
Copyright Year
2017
Publisher
Springer Singapore
Book
Advanced Multimedia and Ubiquitous Engineering

Print ISBN: 978-981-10-5040-4

Electronic ISBN: 978-981-10-5041-1

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-5041-1_57

Premium Partner

    Image Credits