Document Organization using Naive Bayes Related Classifier
R.Sathish Babu1, R.Nagarajan2
1R.Sathish Babu, Assistant Professor, Department of Computer and Information Science, Annamalai University, Annamalai Nagar, India.
2Dr. R. Nagarajan, Assistant Professor, Department of Computer and Information Science, Annamalai University, Annamalai Nagar, India.
Manuscript received on January 17, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 2128-2132 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1539029420/2020©BEIESP | DOI: 10.35940/ijitee.D1539.029420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Document organization is necessary for better utilization of documents. The major problem of organization online documents is so complex because documents should be grouped into its appropriate group during its appearance on the web. Classification is one of the best solutions to organize the documents. Naive Bayes categorization is playing a vital role in document organization. It is one of the simplest probabilistic Bayesian categorization and assumption that the effect of an attribute value on a given category is independent of the values. The document classification is the essential task of organization and necessary for efficient control of textual fact systems. The files may be classified as unconfirmed, supervised and semi supervised methods. In this paper, to review and study of various types of document organization approach using naive Bayesian classification and other related existing document organization methods.
Keywords: Bayes, Document, Classification, Organization, Web Classification and Neural Network.
Scope of the Article: Classification