Fast context-free grammar parsing requires fast boolean matrix multiplication

Author:

Lee Lillian1

Affiliation:

1. Cornell University, Ithaca, New York

Abstract

In 1975, Valiant showed that Boolean matrix multiplication can be used for parsing context-free grammars (CFGs), yielding the asympotically fastest (although not practical) CFG parsing algorithm known. We prove a dual result: any CFG parser with time complexity O ( gn 3-∈ ), where g is the size of the grammar and n is the length of the input string, can be efficiently converted into an algorithm to multiply m × m Boolean matrices in time O ( m 3-∈/3 ). Given that practical, substantially subcubic Boolean matrix multiplication algorithms have been quite difficult to find, we thus explain why there has been little progress in developing practical, substantially subcubic general CFG parsers. In proving this result, we also develop a formalization of the notion of parsing.

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software

Reference31 articles.

1. On economical construction of the transitive closure of an oriented graph;ARLAZAROV V. L.;Soviet Math. Dokl.,1970

2. Extra High Speed Matrix Multiplication on the Cray-2

3. Three models for the description of language;CHOMSKY N.;IRE Trans. Inf. Theory,1956

Cited by 64 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms;Proceedings of the 56th Annual ACM Symposium on Theory of Computing;2024-06-10

2. Faster Combinatorial k-Clique Algorithms;Lecture Notes in Computer Science;2024

3. An Improved Algorithm for The k -Dyck Edit Distance Problem;ACM Transactions on Algorithms;2023-10-19

4. On computing discretized Ricci curvatures of graphs: Local algorithms and (localized) fine-grained reductions;Theoretical Computer Science;2023-10

5. CFL/Dyck Reachability;ACM SIGLOG News;2022-10

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3