Doratossadat Dastgheib


2022

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Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving
Doratossadat Dastgheib | Ehsaneddin Asgari
Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing

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.