数学语言处理导论:非正式证明、文字问题和辅助任务

IF 4.2 1区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Transactions of the Association for Computational Linguistics Pub Date : 2023-01-01 DOI:10.1162/tacl_a_00594

Jordan Meadows, André Freitas

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引用次数: 1

摘要

数学和科学中的自动化发现将需要复杂的信息提取和抽象推理方法，包括能够令人信服地处理数学元素和自然语言之间关系的模型，以产生具有现实世界价值的问题解决方案。我们分析了近年来数学语言处理方法在五个战略子领域(标识符定义提取、公式检索、自然语言前提选择、数学单词问题解决和非正式定理证明)，强调了流行的方法、现有的局限性、总体趋势和未来研究的有希望的途径。

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Introduction to Mathematical Language Processing: Informal Proofs, Word Problems, and Supporting Tasks

Abstract Automating discovery in mathematics and science will require sophisticated methods of information extraction and abstract reasoning, including models that can convincingly process relationships between mathematical elements and natural language, to produce problem solutions of real-world value. We analyze mathematical language processing methods across five strategic sub-areas (identifier-definition extraction, formula retrieval, natural language premise selection, math word problem solving, and informal theorem proving) from recent years, highlighting prevailing methodologies, existing limitations, overarching trends, and promising avenues for future research.

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来源期刊

Transactions of the Association for Computational Linguistics Multiple-

CiteScore

32.60

自引率

4.60%

发文量

审稿时长

8 weeks

期刊介绍： The highly regarded quarterly journal Computational Linguistics has a companion journal called Transactions of the Association for Computational Linguistics. This open access journal publishes articles in all areas of natural language processing and is an important resource for academic and industry computational linguists, natural language processing experts, artificial intelligence and machine learning investigators, cognitive scientists, speech specialists, as well as linguists and philosophers. The journal disseminates work of vital relevance to these professionals on an annual basis.