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Advances in Conceptual Modeling

Overview of attention for book
Cover of 'Advances in Conceptual Modeling'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 A Capability-Driven Development Approach for Requirements and Business Process Modeling
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    Chapter 2 Grounding for Ontological Architecture Quality: Metaphysical Choices
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    Chapter 3 A Model-Driven Engineering Approach for the Well-Being of Ageing People
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    Chapter 4 The Cultural Background and Support for Smart Web Information Systems
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    Chapter 5 Walmart Online Grocery Personalization: Behavioral Insights and Basket Recommendations
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    Chapter 6 Searching for Optimal Configurations Within Large-Scale Models: A Cloud Computing Domain
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    Chapter 7 A Link-Density-Based Algorithm for Finding Communities in Social Networks
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    Chapter 8 Searching for Patterns in Sequential Data: Functionality and Performance Assessment of Commercial and Open-Source Systems
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    Chapter 9 Analysis of Natural and Technogenic Safety of the Krasnoyarsk Region Based on Data Mining Techniques
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    Chapter 10 From Design to Visualization of Spatial OLAP Applications: A First Prototyping Methodology
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    Chapter 11 Bridging User Story Sets with the Use Case Model
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    Chapter 12 A Study on Tangible Participative Enterprise Modelling
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    Chapter 13 Bridging the Requirements Engineering and Business Analysis Toward a Unified Knowledge Framework
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    Chapter 14 An Exploratory Analysis on the Comprehension of 3D and 4D Ontology-Driven Conceptual Models
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    Chapter 15 Data Quality Problems When Integrating Genomic Information
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    Chapter 16 The Design of a Core Value Ontology Using Ontology Patterns
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    Chapter 17 Advances in Conceptual Modeling
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    Chapter 18 Human Factors in the Adoption of Model-Driven Engineering: An Educator’s Perspective
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    Chapter 19 Learning Pros and Cons of Model-Driven Development in a Practical Teaching Experience
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    Chapter 20 Towards Provable Security of Dynamic Source Routing Protocol and Its Applications
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    Chapter 21 A Tool for Analyzing Variability Based on Functional Requirements and Testing Artifacts
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 (54th percentile)

Mentioned by

3 tweeters


3 Dimensions

Readers on

9 Mendeley
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Advances in Conceptual Modeling
Published by
Lecture notes in computer science, October 2016
DOI 10.1007/978-3-319-47717-6
978-3-31-947716-9, 978-3-31-947717-6

Poaka, Vladivy, Hartmann, Sven, Ma, Hui, Steinmetz, Dietrich


Sebastian Link, Juan Carlos Trujillo

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 1 11%
Student > Master 1 11%
Unknown 7 78%
Readers by discipline Count As %
Computer Science 1 11%
Social Sciences 1 11%
Unknown 7 78%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 November 2018.
All research outputs
of 23,335,153 outputs
Outputs from Lecture notes in computer science
of 8,158 outputs
Outputs of similar age
of 321,244 outputs
Outputs of similar age from Lecture notes in computer science
of 478 outputs
Altmetric has tracked 23,335,153 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 8,158 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 50% 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 321,244 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 478 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 54% of its contemporaries.