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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
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    Chapter 2 RDF Graph Visualization by Interpreting Linked Data as Knowledge
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    Chapter 3 Linked Open Vocabulary Recommendation Based on Ranking and Linked Open Data
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    Chapter 4 Heuristic-Based Configuration Learning for Linked Data Instance Matching
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    Chapter 5 Alignment Aware Linked Data Compression
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    Chapter 6 ERA-RJN: A SPARQL-Rank Based Top-k Join Query Optimization
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    Chapter 7 CNME: A System for Chinese News Meta-Data Extraction
  9. Altmetric Badge
    Chapter 8 Bootstrapping Yahoo! Finance by Wikipedia for Competitor Mining
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    Chapter 9 Leveraging Chinese Encyclopedia for Weakly Supervised Relation Extraction
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    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
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    Chapter 14 Identifying an Agent’s Preferences Toward Similarity Measures in Description Logics
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    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
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    Chapter 19 Meta-Level Properties for Reasoning on Dynamic Data
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    Chapter 20 Distance-Based Ranking of Negative Answers
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    Chapter 21 Contrasting RDF Stream Processing Semantics
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    Chapter 22 Towards an Enterprise Entity Hub: Integration of General and Enterprise Knowledge
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    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 (81st percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

13 tweeters
2 Facebook pages

Readers on

10 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Semantic Technology
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-31676-5
978-3-31-931675-8, 978-3-31-931676-5

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

Twitter Demographics

The data shown below were collected from the profiles of 13 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 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

This research output has an Altmetric Attention Score of 9. 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
of 14,574,484 outputs
Outputs from Lecture notes in computer science
of 7,465 outputs
Outputs of similar age
of 264,199 outputs
Outputs of similar age from Lecture notes in computer science
of 88 outputs
Altmetric has tracked 14,574,484 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,465 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 90% 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 264,199 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 81% of its contemporaries.
We're also able to compare this research output to 88 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 94% of its contemporaries.