Mathematical word problem categorization using Machine Learning

Authors(2) :-Basanti Pal Nandi, Poonam Ahuja Narang

Text categorization is a fundamental processing of Natural Language task. Mathematical word problem has a wide variety of classes to categorize, for the further processing of word problems. The classification of word problems plays an important role for text categorization, prediction of algebraic equation for a particular problem in the segment. Word problem classification will be a step towards word problem solving automatically. In this paper comparison of machine learning classifiers such as SVM, Decision Tree, k-Nearest Neighbour, Neural Network and Convolutional Neural Network are used for classification of four types of mathematical problems taking from elementary grade level. Addition, Subtraction, Multiplication and Division problems are the categories chosen from class 3 and class 4 mathematics workbook.

Authors and Affiliations

Basanti Pal Nandi
CSE, Guru Tegh Bahdur Institute of Technology, New Delhi, Delhi, India
Poonam Ahuja Narang
CSE, Guru Tegh Bahdur Institute of Technology, New Delhi, Delhi, India

Word Problem, Deep Learning, Machine Learning

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Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 623-626
Manuscript Number : CSEIT1725136
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Basanti Pal Nandi, Poonam Ahuja Narang, "Mathematical word problem categorization using Machine Learning", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.623-626, September-October-2017.
Journal URL : http://ijsrcseit.com/CSEIT1725136

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