The DeLiVerMATH project - Text analysis in mathematics
Ulf Sch\"oneberg, Wolfram Sperber
TL;DR
This paper presents a machine-based approach utilizing natural language processing to automate key phrase extraction and classification in mathematical texts, aiming to improve content analysis efficiency.
Contribution
It introduces a prototype system for automated content analysis of mathematical texts, addressing the challenge of manual extraction being costly and time-consuming.
Findings
Prototype successfully extracts key phrases from mathematical texts
Automates classification to facilitate retrieval functionalities
Demonstrates potential for scalable mathematical content analysis
Abstract
A high-quality content analysis is essential for retrieval functionalities but the manual extraction of key phrases and classification is expensive. Natural language processing provides a framework to automatize the process. Here, a machine-based approach for the content analysis of mathematical texts is described. A prototype for key phrase extraction and classification of mathematical texts is presented.
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Taxonomy
TopicsMathematics, Computing, and Information Processing · Natural Language Processing Techniques · Advanced Text Analysis Techniques