Mathematical Entity Linking Methods and Applications

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.

Table des matières

Introduction.- Reviews.- Methods.- Applications.- Conclusion & Outlook.

A propos de l'auteur

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.

Détails du produit

• Auteurs: Philipp Scharpf
• Edition: Springer, Berlin
• Langues: Anglais
• Format d'édition: Livre de poche
• Sortie: 01.01.2025
• EAN: 9783658464738
• ISBN: 978-3-658-46473-8
• Pages: 243
• Dimensions: 148 mm x 15 mm x 210 mm
• Poids: 356 g
• Illustrations: XXV, 243 p. 45 illus., 36 illus. in color. Textbook for German language market.
• Catégories: Sciences naturelles, médecine, informatique, technique > Informatique, ordinateurs > Informatique; Informatik, machine learning, Data Mining, Artificial Intelligence, Information Retrieval, Data Mining and Knowledge Discovery, Knowledge based Systems, Question Answering, Wikidata, Entity Linking