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Intelligent Computer Mathematics

Overview of attention for book
Cover of 'Intelligent Computer Mathematics'

Table of Contents

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

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

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4 Dimensions

Readers on

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7 Mendeley
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Chapter title
Comparing Machine Learning Models to Choose the Variable Ordering for Cylindrical Algebraic Decomposition
Chapter number 7
Book title
Intelligent Computer Mathematics
Published in
arXiv, July 2019
DOI 10.1007/978-3-030-23250-4_7
Book ISBNs
978-3-03-023249-8, 978-3-03-023250-4
Authors

Matthew England, Dorian Florescu, England, Matthew, Florescu, Dorian

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 14%
Student > Ph. D. Student 1 14%
Researcher 1 14%
Student > Postgraduate 1 14%
Student > Master 1 14%
Other 0 0%
Unknown 2 29%
Readers by discipline Count As %
Computer Science 2 29%
Mathematics 1 14%
Physics and Astronomy 1 14%
Unknown 3 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 April 2019.
All research outputs
#19,495,804
of 23,978,545 outputs
Outputs from arXiv
#588,045
of 1,010,913 outputs
Outputs of similar age
#262,358
of 349,660 outputs
Outputs of similar age from arXiv
#16,212
of 28,629 outputs
Altmetric has tracked 23,978,545 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,010,913 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 349,660 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28,629 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.