scholarly journals A Document Classification System Using Modified ECCD and Category Weight for each Document

2012 ◽  
Vol 19B (4) ◽  
pp. 237-242
Author(s):  
Chung-Seok Han ◽  
Sang-Yong Park ◽  
Soo-Won Lee
Keyword(s):  
Classification System ◽  
Document Classification

Hindi Text Document Classification System Using SVM and Fuzzy

2018 ◽  
Vol 5 (4) ◽  
pp. 1-31 ◽  
Author(s):  
Shalini Puri ◽  
Satya Prakash Singh
Keyword(s):  
Classification System ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Document Classification ◽  
Data Availability ◽  
Support Vector ◽  
Handwritten Documents ◽  
Text Document ◽  
Survey Report ◽  
Text Document Classification

In recent years, many information retrieval, character recognition, and feature extraction methodologies in Devanagari and especially in Hindi have been proposed for different domain areas. Due to enormous scanned data availability and to provide an advanced improvement of existing Hindi automated systems beyond optical character recognition, a new idea of Hindi printed and handwritten document classification system using support vector machine and fuzzy logic is introduced. This first pre-processes and then classifies textual imaged documents into predefined categories. With this concept, this article depicts a feasibility study of such systems with the relevance of Hindi, a survey report of statistical measurements of Hindi keywords obtained from different sources, and the inherent challenges found in printed and handwritten documents. The technical reviews are provided and graphically represented to compare many parameters and estimate contents, forms and classifiers used in various existing techniques.

A Fuzzy Matching based Image Classification System for Printed and Handwritten Text Documents

2020 ◽  
Vol 13 (2) ◽  
pp. 155-194
Author(s):  
Shalini Puri ◽  
Satya Prakash Singh
Keyword(s):  
Image Classification ◽  
Classification System ◽  
Word Association ◽  
Computation Time ◽  
Document Classification ◽  
Efficient Manner ◽  
Text Documents ◽  
Handwritten Text ◽  
Fuzzy Matching ◽  
Character Classification

This article proposes a bi-leveled image classification system to classify printed and handwritten English documents into mutually exclusive predefined categories. The proposed system follows the steps of preprocessing, segmentation, feature extraction, and SVM based character classification at level 1, and word association and fuzzy matching based document classification at level 2. The system architecture and its modular structure discuss various task stages and their functionalities. Further, a case study on document classification is discussed to show the internal score computations of words and keywords with fuzzy matching. The experiments on proposed system illustrate that the system achieves promising results in the time-efficient manner and achieves better accuracy with less computation time for printed documents than handwritten ones. Finally, the performance of the proposed system is compared with the existing systems and it is observed that proposed system performs better than many other systems.

scholarly journals User Behavior Analysis of the Open-Ended Document Classification System

2006 ◽  
pp. 1089-1095 ◽  
Author(s):  
Yang Sok Kim ◽  
Byeong Ho Kang ◽  
Young Ju Choi ◽  
SungSik Park ◽  
Gil Cheol Park ◽  
...  
Keyword(s):  
Behavior Analysis ◽  
Classification System ◽  
User Behavior ◽  
Document Classification ◽  
User Behavior Analysis

A fully visual based business document classification system

2014 ◽  
Author(s):  
Ignazio Infantino ◽  
Umberto Maniscalco ◽  
Dario Stabile ◽  
Filippo Vella
Keyword(s):  
Classification System ◽  
Document Classification
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