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Active Conceptual Modeling of Learning

Overview of attention for book
Cover of 'Active Conceptual Modeling of Learning'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Overview of Papers in 2006 Active Conceptual Modeling of Learning (ACM-L) Workshop
  3. Altmetric Badge
    Chapter 2 Architecture for Active Conceptual Modeling of Learning
  4. Altmetric Badge
    Chapter 3 Understanding the Semantics of Data Provenance to Support Active Conceptual Modeling
  5. Altmetric Badge
    Chapter 4 Adaptive and Context-Aware Reconciliation of Reactive and Pro-active Behavior in Evolving Systems
  6. Altmetric Badge
    Chapter 5 A Common Core for Active Conceptual Modeling for Learning from Surprises
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    Chapter 6 Actively Evolving Conceptual Models for Mini-World and Run-Time Environment Changes
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    Chapter 7 Achievements and Problems of Conceptual Modelling
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    Chapter 8 Metaphor Modeling on the Semantic Web
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    Chapter 9 Schema Changes and Historical Information in Conceptual Models in Support of Adaptive Systems
  11. Altmetric Badge
    Chapter 10 Using Active Modeling in Counterterrorism
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    Chapter 11 To Support Emergency Management by Using Active Modeling: A Case of Hurricane Katrina
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    Chapter 12 Using Ontological Modeling in a Context-Aware Summarization System to Adapt Text for Mobile Devices
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    Chapter 13 Accommodating Streams to Support Active Conceptual Modeling of Learning from Surprises
  15. Altmetric Badge
    Chapter 14 Approaches to the Active Conceptual Modelling of Learning
  16. Altmetric Badge
    Chapter 15 Spatio-temporal and Multi-representation Modeling: A Contribution to Active Conceptual Modeling
  17. Altmetric Badge
    Chapter 16 Postponing Schema Definition: Low Instance-to-Entity Ratio ( LItER ) Modelling
  18. Altmetric Badge
    Chapter 17 Research Issues in Active Conceptual Modeling of Learning: Summary of Panel Discussions in Two Workshops (May 2006) and (November 2006)
Attention for Chapter 3: Understanding the Semantics of Data Provenance to Support Active Conceptual Modeling
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
56 Mendeley
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Chapter title
Understanding the Semantics of Data Provenance to Support Active Conceptual Modeling
Chapter number 3
Book title
Active Conceptual Modeling of Learning
Published in
ADS, November 2006
DOI 10.1007/978-3-540-77503-4_3
Book ISBNs
978-3-54-077502-7, 978-3-54-077503-4
Authors

Sudha Ram, Jun Liu, Ram, Sudha, Liu, Jun

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 9%
Portugal 1 2%
Brazil 1 2%
Ireland 1 2%
Ukraine 1 2%
Czechia 1 2%
Unknown 46 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 36%
Student > Master 10 18%
Researcher 7 13%
Professor > Associate Professor 4 7%
Student > Doctoral Student 3 5%
Other 9 16%
Unknown 3 5%
Readers by discipline Count As %
Computer Science 32 57%
Business, Management and Accounting 6 11%
Engineering 4 7%
Agricultural and Biological Sciences 2 4%
Earth and Planetary Sciences 2 4%
Other 6 11%
Unknown 4 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 11 January 2022.
All research outputs
#5,753,963
of 22,851,489 outputs
Outputs from ADS
#7,322
of 37,383 outputs
Outputs of similar age
#20,131
of 69,881 outputs
Outputs of similar age from ADS
#32
of 139 outputs
Altmetric has tracked 22,851,489 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 37,383 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 79% 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 69,881 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 70% of its contemporaries.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.