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The Semantic Web – ISWC 2019

Overview of attention for book
Cover of 'The Semantic Web – ISWC 2019'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 The KEEN Universe
  3. Altmetric Badge
    Chapter 2 VLog: A Rule Engine for Knowledge Graphs
  4. Altmetric Badge
    Chapter 3 ArCo: The Italian Cultural Heritage Knowledge Graph
  5. Altmetric Badge
    Chapter 4 Making Study Populations Visible Through Knowledge Graphs
  6. Altmetric Badge
    Chapter 5 LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia
  7. Altmetric Badge
    Chapter 6 SEO: A Scientific Events Data Model
  8. Altmetric Badge
    Chapter 7 DBpedia FlexiFusion the Best of Wikipedia > Wikidata > Your Data
  9. Altmetric Badge
    Chapter 8 The Microsoft Academic Knowledge Graph: A Linked Data Source with 8 Billion Triples of Scholarly Data
  10. Altmetric Badge
    Chapter 9 The RealEstateCore Ontology
  11. Altmetric Badge
    Chapter 10 FoodKG: A Semantics-Driven Knowledge Graph for Food Recommendation
  12. Altmetric Badge
    Chapter 11 BTC-2019: The 2019 Billion Triple Challenge Dataset
  13. Altmetric Badge
    Chapter 12 Extending the YAGO2 Knowledge Graph with Precise Geospatial Knowledge
  14. Altmetric Badge
    Chapter 13 The SEPSES Knowledge Graph: An Integrated Resource for Cybersecurity
  15. Altmetric Badge
    Chapter 14 SemanGit: A Linked Dataset from git
  16. Altmetric Badge
    Chapter 15 Squerall: Virtual Ontology-Based Access to Heterogeneous and Large Data Sources
  17. Altmetric Badge
    Chapter 16 List.MID: A MIDI-Based Benchmark for Evaluating RDF Lists
  18. Altmetric Badge
    Chapter 17 A Scalable Framework for Quality Assessment of RDF Datasets
  19. Altmetric Badge
    Chapter 18 QaldGen: Towards Microbenchmarking of Question Answering Systems over Knowledge Graphs
  20. Altmetric Badge
    Chapter 19 Sparklify: A Scalable Software Component for Efficient Evaluation of SPARQL Queries over Distributed RDF Datasets
  21. Altmetric Badge
    Chapter 20 ClaimsKG: A Knowledge Graph of Fact-Checked Claims
  22. Altmetric Badge
    Chapter 21 CoCoOn: Cloud Computing Ontology for IaaS Price and Performance Comparison
  23. Altmetric Badge
    Chapter 22 Semantically-Enabled Optimization of Digital Marketing Campaigns
  24. Altmetric Badge
    Chapter 23 An End-to-End Semantic Platform for Nutritional Diseases Management
  25. Altmetric Badge
    Chapter 24 VLX-Stories: Building an Online Event Knowledge Base with Emerging Entity Detection
  26. Altmetric Badge
    Chapter 25 Personalized Knowledge Graphs for the Pharmaceutical Domain
  27. Altmetric Badge
    Chapter 26 Use of OWL and Semantic Web Technologies at Pinterest
  28. Altmetric Badge
    Chapter 27 An Assessment of Adoption and Quality of Linked Data in European Open Government Data
  29. Altmetric Badge
    Chapter 28 Easy Web API Development with SPARQL Transformer
  30. Altmetric Badge
    Chapter 29 Benefit Graph Extraction from Healthcare Policies
  31. Altmetric Badge
    Chapter 30 Knowledge Graph Embedding for Ecotoxicological Effect Prediction
  32. Altmetric Badge
    Chapter 31 Improving Editorial Workflow and Metadata Quality at Springer Nature
  33. Altmetric Badge
    Chapter 32 A Pay-as-you-go Methodology to Design and Build Enterprise Knowledge Graphs from Relational Databases
Attention for Chapter 31: Improving Editorial Workflow and Metadata Quality at Springer Nature
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
1 blog
twitter
12 X users

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
17 Mendeley
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Chapter title
Improving Editorial Workflow and Metadata Quality at Springer Nature
Chapter number 31
Book title
The Semantic Web – ISWC 2019
Published in
arXiv, October 2019
DOI 10.1007/978-3-030-30796-7_31
Book ISBNs
978-3-03-030795-0, 978-3-03-030796-7
Authors

Angelo A. Salatino, Francesco Osborne, Aliaksandr Birukou, Enrico Motta, Salatino, Angelo, Osborne, Francesco, Birukou, Aliaksandr, Motta, Enrico, Salatino, Angelo A.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 29%
Other 2 12%
Professor 2 12%
Lecturer 1 6%
Student > Bachelor 1 6%
Other 2 12%
Unknown 4 24%
Readers by discipline Count As %
Computer Science 9 53%
Business, Management and Accounting 1 6%
Agricultural and Biological Sciences 1 6%
Social Sciences 1 6%
Unknown 5 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 29 April 2021.
All research outputs
#2,569,177
of 24,980,180 outputs
Outputs from arXiv
#43,783
of 1,018,032 outputs
Outputs of similar age
#53,318
of 369,208 outputs
Outputs of similar age from arXiv
#1,317
of 28,686 outputs
Altmetric has tracked 24,980,180 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,018,032 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 95% of its peers.
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 369,208 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 28,686 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.