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A review of methods for automatic understanding of natural language mathematical problems

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Abstract

This article addresses the problem of understanding mathematics described in natural language. Research in this area dates back to early 1960s. Several systems have so far been proposed to involve machines to solve mathematical problems of various domains like algebra, geometry, physics, mechanics, etc. This correspondence provides a state of the art technical review of these systems and approaches proposed by different research groups. A unified architecture that has been used in most of these approaches is identified and differences among the systems are highlighted. Significant achievements of each method are pointed out. Major strengths and weaknesses of the approaches are also discussed. Finally, present efforts and future trends in this research area are presented.

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Authors and Affiliations

  1. Department of IT, RCC Institute of Information Technology, Canal South Road, Kolkata, 700015, India

    Anirban Mukherjee

  2. Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, 203, B.T. Road, Kolkata, 700108, India

    Utpal Garain

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  1. Anirban Mukherjee
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  2. Utpal Garain
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Correspondence to Anirban Mukherjee.

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Mukherjee, A., Garain, U. A review of methods for automatic understanding of natural language mathematical problems. Artif Intell Rev 29, 93–122 (2008). https://doi.org/10.1007/s10462-009-9110-0

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