@inproceedings{dastgheib-asgari-2022-keyword,
title = "Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving",
author = "Dastgheib, Doratossadat and
Asgari, Ehsaneddin",
editor = "Ustalov, Dmitry and
Gao, Yanjun and
Panchenko, Alexander and
Valentino, Marco and
Thayaparan, Mokanarangan and
Nguyen, Thien Huu and
Penn, Gerald and
Ramesh, Arti and
Jana, Abhik",
booktitle = "Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.textgraphs-1.14",
pages = "124--126",
abstract = "Extraction of supportive premises for a mathematical problem can contribute to profound success in improving automatic reasoning systems. One bottleneck in automated theorem proving is the lack of a proper semantic information retrieval system for mathematical texts. In this paper, we show the effect of keyword extraction in the natural language premise selection (NLPS) shared task proposed in TextGraph-16 that seeks to select the most relevant sentences supporting a given mathematical statement.",
}
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%0 Conference Proceedings
%T Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving
%A Dastgheib, Doratossadat
%A Asgari, Ehsaneddin
%Y Ustalov, Dmitry
%Y Gao, Yanjun
%Y Panchenko, Alexander
%Y Valentino, Marco
%Y Thayaparan, Mokanarangan
%Y Nguyen, Thien Huu
%Y Penn, Gerald
%Y Ramesh, Arti
%Y Jana, Abhik
%S Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F dastgheib-asgari-2022-keyword
%X Extraction of supportive premises for a mathematical problem can contribute to profound success in improving automatic reasoning systems. One bottleneck in automated theorem proving is the lack of a proper semantic information retrieval system for mathematical texts. In this paper, we show the effect of keyword extraction in the natural language premise selection (NLPS) shared task proposed in TextGraph-16 that seeks to select the most relevant sentences supporting a given mathematical statement.
%U https://aclanthology.org/2022.textgraphs-1.14
%P 124-126
Markdown (Informal)
[Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving](https://aclanthology.org/2022.textgraphs-1.14) (Dastgheib & Asgari, TextGraphs 2022)
ACL