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The Semantic Web

Overview of attention for book
Cover of 'The Semantic Web'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Applying Semantic Web Technologies to Assess Maintenance Tasks from Operational Interruptions: A Use-Case at Airbus
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    Chapter 2 Modeling Company Risk and Importance in Supply Graphs
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    Chapter 3 Enhancing white-box machine learning processes by incorporating semantic background knowledge
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    Chapter 4 BalOnSe: Temporal Aspects of Dance Movement and Its Ontological Representation
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    Chapter 5 Reasoning on Engineering Knowledge: Applications and Desired Features
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    Chapter 6 A Compressed, Inference-Enabled Encoding Scheme for RDF Stream Processing
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    Chapter 7 From Data to City Indicators: A Knowledge Graph for Supporting Automatic Generation of Dashboards
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    Chapter 8 Ontology-Driven Unified Governance in Software Engineering: The PoolParty Case Study
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    Chapter 9 A Hypercat-Enabled Semantic Internet of Things Data Hub
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    Chapter 10 ArmaTweet: Detecting Events by Semantic Tweet Analysis
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    Chapter 11 smartAPI: Towards a More Intelligent Network of Web APIs
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    Chapter 12 Automating the Dynamic Interactions of Self-governed Components in Distributed Architectures
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    Chapter 13 Building and Processing a Knowledge-Graph for Legal Data
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    Chapter 14 Ontology Matching Algorithms for Data Model Alignment in Big Data
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    Chapter 15 Ontology-Based Data Access Mapping Generation Using Data, Schema, Query, and Mapping Knowledge
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    Chapter 16 Engaging Librarians in the Process of Interlinking RDF Resources
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    Chapter 17 A Knowledge-Based Framework for Improving Accessibility of Web Sites
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    Chapter 18 Iterative Approach for Information Extraction and Ontology Learning from Textual Aviation Safety Reports
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    Chapter 19 Integrative Data Management for Reproducibility of Microscopy Experiments
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    Chapter 20 Towards an Open Extensible Framework for Empirical Benchmarking of Data Management Solutions: LITMUS
  22. Altmetric Badge
    Chapter 21 Enhancing White-Box Machine Learning Processes by Incorporating Semantic Background Knowledge
Overall attention for this book and its chapters
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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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

blogs
1 blog
twitter
5 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
32 Mendeley
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Title
The Semantic Web
Published by
Lecture notes in computer science, January 2017
DOI 10.1007/978-3-319-58451-5
URN
urn:isbn:978-3-319-58451-5
ISBNs
978-3-31-958450-8, 978-3-31-958451-5
Authors

Ongenae, Femke, De Backere, Femke, Mahieu, Christof, De Pestel, Stijn, Nelis, Jelle, Simoens, Pieter, De Turck, Filip, Bonte, Pieter, Schaballie, Jeroen, Vancroonenburg, W., Vankeirsbilck, Bert, Van Herwegen, Joachim, Verborgh, Ruben, Mannens, Erik, Taelman, Ruben, Vander Sande, Miel, Vandewiele, Gilles

Editors

Eva Blomqvist, Diana Maynard, Aldo Gangemi, Rinke Hoekstra, Pascal Hitzler, Olaf Hartig

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 28%
Student > Master 5 16%
Student > Bachelor 3 9%
Lecturer > Senior Lecturer 2 6%
Researcher 2 6%
Other 2 6%
Unknown 9 28%
Readers by discipline Count As %
Computer Science 13 41%
Engineering 5 16%
Business, Management and Accounting 2 6%
Arts and Humanities 1 3%
Decision Sciences 1 3%
Other 1 3%
Unknown 9 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 15 July 2023.
All research outputs
#3,402,256
of 25,374,647 outputs
Outputs from Lecture notes in computer science
#659
of 8,159 outputs
Outputs of similar age
#64,185
of 421,653 outputs
Outputs of similar age from Lecture notes in computer science
#27
of 152 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,159 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 91% 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 421,653 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 84% of its contemporaries.
We're also able to compare this research output to 152 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.