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Semantic Technology

Overview of attention for book
Cover of 'Semantic Technology'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Modeling and Querying Spatial Data Warehouses on the Semantic Web
  3. Altmetric Badge
    Chapter 2 RDF Graph Visualization by Interpreting Linked Data as Knowledge
  4. Altmetric Badge
    Chapter 3 Linked Open Vocabulary Recommendation Based on Ranking and Linked Open Data
  5. Altmetric Badge
    Chapter 4 Heuristic-Based Configuration Learning for Linked Data Instance Matching
  6. Altmetric Badge
    Chapter 5 Alignment Aware Linked Data Compression
  7. Altmetric Badge
    Chapter 6 ERA-RJN: A SPARQL-Rank Based Top-k Join Query Optimization
  8. Altmetric Badge
    Chapter 7 CNME: A System for Chinese News Meta-Data Extraction
  9. Altmetric Badge
    Chapter 8 Bootstrapping Yahoo! Finance by Wikipedia for Competitor Mining
  10. Altmetric Badge
    Chapter 9 Leveraging Chinese Encyclopedia for Weakly Supervised Relation Extraction
  11. Altmetric Badge
    Chapter 10 Improving Knowledge Base Completion by Incorporating Implicit Information
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    Chapter 11 Automatic Generation of Semantic Data for Event-Related Medical Guidelines
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    Chapter 12 Evaluating and Comparing Web-Scale Extracted Knowledge Bases in Chinese and English
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    Chapter 13 Computing the Semantic Similarity of Resources in DBpedia for Recommendation Purposes
  15. Altmetric Badge
    Chapter 14 Identifying an Agent’s Preferences Toward Similarity Measures in Description Logics
  16. Altmetric Badge
    Chapter 15 A Contrastive Study on Semantic Prosodies of Minimal Degree Adverbs in Chinese and English
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    Chapter 16 A Graph Traversal Based Approach to Answer Non-Aggregation Questions over DBpedia
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    Chapter 17 Answer Type Identification for Question Answering
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    Chapter 18 PROSE: A Plugin-Based Paraconsistent OWL Reasoner
  20. Altmetric Badge
    Chapter 19 Meta-Level Properties for Reasoning on Dynamic Data
  21. Altmetric Badge
    Chapter 20 Distance-Based Ranking of Negative Answers
  22. Altmetric Badge
    Chapter 21 Contrasting RDF Stream Processing Semantics
  23. Altmetric Badge
    Chapter 22 Towards an Enterprise Entity Hub: Integration of General and Enterprise Knowledge
  24. Altmetric Badge
    Chapter 23 Ontology Development for Interoperable Database to Share Data in Service Fields
  25. Altmetric Badge
    Chapter 24 Efficiently Finding Paths Between Classes to Build a SPARQL Query for Life-Science Databases
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 (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
12 X users
facebook
2 Facebook pages

Readers on

mendeley
10 Mendeley
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Title
Semantic Technology
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-31676-5
ISBNs
978-3-31-931675-8, 978-3-31-931676-5
Editors

Guilin Qi, Kouji Kozaki, Jeff Z. Pan, Siwei Yu

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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 30%
Professor > Associate Professor 1 10%
Researcher 1 10%
Student > Doctoral Student 1 10%
Unknown 4 40%
Readers by discipline Count As %
Computer Science 4 40%
Medicine and Dentistry 1 10%
Engineering 1 10%
Unknown 4 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 19 August 2018.
All research outputs
#4,516,943
of 25,211,948 outputs
Outputs from Lecture notes in computer science
#973
of 8,153 outputs
Outputs of similar age
#71,127
of 405,878 outputs
Outputs of similar age from Lecture notes in computer science
#143
of 581 outputs
Altmetric has tracked 25,211,948 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,153 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 well, scoring higher than 88% 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 405,878 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 82% of its contemporaries.
We're also able to compare this research output to 581 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.