Title
A Framework For Solving Explicit Arithmetic Word Problems And Proving Plane Geometry Theorems
Abstract
This paper presents a framework for solving math problems stated in a natural language (NL) and applies the framework to develop algorithms for solving explicit arithmetic word problems and proving plane geometry theorems. We focus on problem understanding, that is, the transformation of a NL description of a math problem to a formal representation. We view this as a relation extraction problem, and adopt a greedy algorithm to extract the mathematical relations using a syntax-semantics model, which is a set of patterns describing how a syntactic pattern is mapped to its formal semantics. Our method yields a human readable solution that shows how the mathematical relations are extracted one at a time. We apply our framework to solve arithmetic word problems and prove plane geometry theorems. For arithmetic word problems, the extracted relations are transformed into a system of equations, and the equations are then solved to produce the solution. For plane geometry theorems, these extracted relations are input to an inference system to generate the proof. We evaluate our approach on a set of arithmetic word problems stated in Chinese, and two sets of plane geometry theorems stated in Chinese and English. Our algorithms achieve high accuracies on these datasets and they also show some desirable properties such as brevity of algorithm description and legibility of algorithm actions.
Year
DOI
Venue
2019
10.1142/S0218001419400056
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Automatic solver, relation extraction, syntax-semantic model, arithmetic word problems, plane geometry theorems
Legibility,System of linear equations,Word problem (mathematics education),Plane (geometry),Arithmetic,Greedy algorithm,Natural language,Syntax,Mathematics,Relationship extraction
Journal
Volume
Issue
ISSN
33
7
0218-0014
Citations 
PageRank 
References 
0
0.34
5
Authors
5
Name
Order
Citations
PageRank
Xinguo Yu144340.77
Mingshu Wang223.08
Wenbin Gan301.69
Bin He401.35
Nan Ye514912.60