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Documents from Science, Technology, Engineering, and Mathematics (STEM) disciplines usually contain many mathematical formulas alongside text [163]. Mathematical Information Retrieval (MathIR) systems, such as Document Recommender (DocRec), Mathematical Question Answering (MathQA), Mathematical Question Generation (MathQG), and Automatic Mathematical Document Classification (AMathDC) need to process and query the semantics of those mathematical formulas systematically [162]. This requires linking mathematical language expressions, such as formulas and identifiers (variables with no fixed value [170]) or constants to semantic concepts with natural language names and unique groundings in a knowledge base (KB) or knowledge graph (KG), e.g., Wikidata.

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Introduction

  • 章节

  • 发表日期：

    2025年

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  • Philipp Scharpf

摘要

Documents from Science, Technology, Engineering, and Mathematics (STEM) disciplines usually contain many mathematical formulas alongside text [163]. Mathematical Information Retrieval (MathIR) systems, such as Document Recommender (DocRec), Mathematical Question Answering (MathQA), Mathematical Question Generation (MathQG), and Automatic Mathematical Document Classification (AMathDC) need to process and query the semantics of those mathematical formulas systematically [162]. This requires linking mathematical language expressions, such as formulas and identifiers (variables with no fixed value [170]) or constants to semantic concepts with natural language names and unique groundings in a knowledge base (KB) or knowledge graph (KG), e.g., Wikidata.