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Document Categorization using Improved KNN Classification

Author(s):

Neha , KURUKSHETRA UNIVERSITY; R. K Chauhan, KURUKSHETRA UNIVERSITY

Keywords:

Data Mining, Improved KNN, Centre Prediction, TF-IDF, Confusion Matrix, Euclidian Distance

Abstract

Document categorization is the method of classifying the documents from mixed documents into particular specific documents such that they belong to the same classes. Classification is a data mining technique used to predict group membership for data instances. The relevance of keywords in documents and text mining has become very essential. An easy way of storing creates the need for a convenient way of retrieval which simplifies that what is the use of storing documents if they cannot be found. Resultantly, categorization of documents has been applied to make it easier to find relevant information. Classifying the documents is more convenient and virtuous. Thus, the main aim of this research is to design an improved KNN classifying technique so as to classify large sets of documents with improved accuracy in lesser time in terms of F-measure and G-measure.

Other Details

Paper ID: IJSRDV4I50042
Published in: Volume : 4, Issue : 5
Publication Date: 01/08/2016
Page(s): 832-834

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