The Most Uncreative Examinee: A First Step Toward Wide Coverage Natural Language Math Problem Solving
Abstract
We report on a project aiming at developing a system that solves a wide range of math problems written in natural language. In the system, formal analysis of natural language semantics is coupled with automated reasoning technologies including computer algebra, using logic as their common language. We have developed a prototype system that accepts as its input a linguistically annotated problem text. Using the prototype system as a reference point, we analyzed real university entrance examination problems from the viewpoint of end-to-end automated reasoning. Further, evaluation on entrance exam mock tests revealed that an optimistic estimate of the system’s performance already matches human averages on a few test sets.
Cite
Text
Matsuzaki et al. "The Most Uncreative Examinee: A First Step Toward Wide Coverage Natural Language Math Problem Solving." AAAI Conference on Artificial Intelligence, 2014. doi:10.1609/AAAI.V28I1.8869Markdown
[Matsuzaki et al. "The Most Uncreative Examinee: A First Step Toward Wide Coverage Natural Language Math Problem Solving." AAAI Conference on Artificial Intelligence, 2014.](https://mlanthology.org/aaai/2014/matsuzaki2014aaai-most/) doi:10.1609/AAAI.V28I1.8869BibTeX
@inproceedings{matsuzaki2014aaai-most,
title = {{The Most Uncreative Examinee: A First Step Toward Wide Coverage Natural Language Math Problem Solving}},
author = {Matsuzaki, Takuya and Iwane, Hidenao and Anai, Hirokazu and Arai, Noriko H.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2014},
pages = {1098-1104},
doi = {10.1609/AAAI.V28I1.8869},
url = {https://mlanthology.org/aaai/2014/matsuzaki2014aaai-most/}
}