A Multi-language Platform for Generating Algebraic Mathematical Word Problems

Liyanage, Vijini, Ranathunga, Surangika

arXiv.org Machine Learning 

--Existing approaches for automatically generating mathematical word problems are deprived of customizability and creativity due to the inherent nature of template-based mechanisms they employ. We present a solution to this problem with the use of deep neural language generation mechanisms. Our approach uses a Character Level Long Short T erm Memory Network (LSTM) to generate word problems, and uses POS (Part of Speech) tags to resolve the constraints found in the generated problems. Our approach is capable of generating Mathematics Word Problems in both English and Sinhala languages with an accuracy over 90%. A Mathematical word problem (MWP) is a mathematical problem expressed in natural language. Unlike other knowledge based question types such as travel or history related questions, MWPs require problem solving ability. In particular, algebraic questions involve sentences to make the questions more deep and inspective. Algebra is a major component of mathematics that is learnt by every student in Ordinary Level (O/L). Simple algebra problems mostly appear in a word format.

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