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Autor(en): 
  • Philipp Scharpf
  • Mathematical Entity Linking Methods and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  April 2025  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / Data Mining / Data Mining and Knowledge Discovery / Entity Linking / Informatik / Information Retrieval / Knowledge based Systems / machine learning
    ISBN:  9783658464738 
    EAN-Code: 
    9783658464738 
    Verlag:  Springer Fachmedien Wiesbaden GmbH 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 210 mm / B 148 mm / D  
    Seiten:  243 
    Illustration:  XXV, 243 p. 45 illus., 36 illus. in color. Textbook for German language market., farbige Illustrationen, schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This research book explores the adaptation of traditional Entity Linking techniques to Mathematical Entity Linking (MathEL) for STEM disciplines, addressing the limitations of current Information Retrieval methods in handling mathematical expressions. By developing and evaluating novel MathEL approaches using AI, Machine Learning, and the Wikidata Knowledge Graph, significant progress is achieved in areas such as Formula Concept recognition, semantic formula search, mathematical question answering, physics exam question generation, and STEM document classification. The study also introduces a suite of open-source Wikimedia MathEL tools, including AnnoMathTeX, MathQA, and PhysWikiQuiz, designed to advance Mathematical Information Retrieval and support innovative applications in academic and educational contexts.

    About the author

    Philipp Scharpf studied physics at ETH Zurich, the University of Zurich and the University of Constance and completed his doctorate in computer science in the field of artificial intelligence at the University of Constance and the University of Göttingen. Since 2022, he has been a freelance consultant for data and AI solutions and a lecturer at the University of Stuttgart for Big Data and Learning Analytics.

      



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