ACIRD: intelligent Internet document organization and retrieval

2002 ◽  
Vol 14 (3) ◽  
pp. 599-614 ◽  
Author(s):  
Shian-Hua Lin ◽  
Meng Chang Chen ◽  
Jan-Ming Ho ◽  
Yueh-Ming Huang
2017 ◽  
Vol 21 (6) ◽  
pp. 480-497 ◽  
Author(s):  
Anna Potocki ◽  
Christine Ros ◽  
Nicolas Vibert ◽  
Jean-François Rouet

Author(s):  
Thomas Seifried ◽  
Matthew Jervis ◽  
Michael Haller ◽  
Masood Masoodian ◽  
Nicolas Villar

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.


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