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Intelligent Computer Mathematics

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Cover of 'Intelligent Computer Mathematics'

Table of Contents

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    Book Overview
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    Chapter 1 Interaction with Formal Mathematical Documents in Isabelle/PIDE
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    Chapter 2 Beginners’ Quest to Formalize Mathematics: A Feasibility Study in Isabelle
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    Chapter 3 Towards a Unified Mathematical Data Infrastructure: Database and Interface Generation
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    Chapter 4 A Tale of Two Set Theories
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    Chapter 5 Relational Data Across Mathematical Libraries
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    Chapter 6 Variadic Equational Matching
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    Chapter 7 Comparing Machine Learning Models to Choose the Variable Ordering for Cylindrical Algebraic Decomposition
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    Chapter 8 Towards Specifying Symbolic Computation
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    Chapter 9 Lemma Discovery for Induction
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    Chapter 10 Experiments on Automatic Inclusion of Some Non-degeneracy Conditions Among the Hypotheses in Locus Equation Computations
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    Chapter 11 Formalization of Dubé’s Degree Bounds for Gröbner Bases in Isabelle/HOL
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    Chapter 12 The Coq Library as a Theory Graph
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    Chapter 13 BNF-Style Notation as It Is Actually Used
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    Chapter 14 MMTTeX: Connecting Content and Narration-Oriented Document Formats
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    Chapter 15 Diagram Combinators in MMT
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    Chapter 16 Inspection and Selection of Representations
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    Chapter 17 A Plugin to Export Coq Libraries to XML
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    Chapter 18 Forms of Plagiarism in Digital Mathematical Libraries
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    Chapter 19 Integrating Semantic Mathematical Documents and Dynamic Notebooks
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    Chapter 20 Explorations into the Use of Word Embedding in Math Search and Math Semantics
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Title
Intelligent Computer Mathematics
Published by
Springer International Publishing, September 2019
DOI 10.1007/978-3-030-23250-4
ISBNs
978-3-03-023249-8, 978-3-03-023250-4
Editors

Kaliszyk, Cezary, Brady, Edwin, Kohlhase, Andrea, Sacerdoti Coen, Claudio

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 3 4%
United Kingdom 2 3%
Russia 1 1%
Germany 1 1%
Portugal 1 1%
Bulgaria 1 1%
Japan 1 1%
United States 1 1%
Austria 1 1%
Other 2 3%
Unknown 53 79%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 24%
Student > Ph. D. Student 10 15%
Unspecified 8 12%
Student > Bachelor 6 9%
Professor 5 7%
Other 22 33%
Readers by discipline Count As %
Computer Science 35 52%
Unspecified 10 15%
Social Sciences 6 9%
Engineering 5 7%
Physics and Astronomy 3 4%
Other 8 12%