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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

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
26 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

Editors

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

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 15%
Student > Master 2 8%
Researcher 1 4%
Student > Bachelor 1 4%
Unknown 18 69%
Readers by discipline Count As %
Computer Science 4 15%
Engineering 2 8%
Business, Management and Accounting 1 4%
Arts and Humanities 1 4%
Unknown 18 69%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 August 2018.
All research outputs
#8,910,613
of 15,533,212 outputs
Outputs from Lecture notes in computer science
#3,827
of 7,577 outputs
Outputs of similar age
#128,797
of 269,050 outputs
Outputs of similar age from Lecture notes in computer science
#63
of 146 outputs
Altmetric has tracked 15,533,212 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,577 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 48th percentile – i.e., 48% 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 269,050 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.