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  • × author_ss:"Schöneberg, U."
  • × year_i:[2010 TO 2020}
  1. Sperber, W.; Schöneberg, U.: Machine-learning methods for classification and content authority control in mathematics (2015) 0.04 
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    Abstract
    The abstracting and reviewing service zbMATH (zbMATH, 1931- ) is the most comprehensive bibliographic database of mathematical literature. The database uses reviews, keywords and classification for content analysis of mathematical publications. Controlled vocabularies and classification schemes are important for a uniform and standardised analysis of the content and precise information retrieval. Over the last few years, the zbMATH team has started developing machine-based concepts and tools to create controlled vocabularies and to improve the Mathematics Subject Classification (MSC) scheme. Concepts of natural language processing and other machine learning methods, especially neural networks, were adapted to the specific requirements of mathematical information, e.g., named mathematical entities and mathematical formulas. The tools are used for key phrase extraction and classification of mathematical publications. Basing on the extracted key phrases, a prototype for a controlled vocabulary for mathematics was created. The tools and the state of the art are described briefly. These activities will help - in cooperation with authority control for authors, series and institutions - to automate the zbMATH workflow and improve the usefulness and information retrieval capabilities of the database.
  2. Schöneberg, U.; Sperber, W.: ¬The DeLiVerMATH project : text analysis in mathematics (2013) 0.01 
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  3. Schöneberg, U.; Gödert, W.: Erschließung mathematischer Publikationen mittels linguistischer Verfahren (2012) 0.01 
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  4. Schöneberg, U.; Sperber, W.: POS tagging and its applications for mathematics (2014) 0.01 
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