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Advances in Intelligent Data Analysis XIV

Overview of attention for book
Cover of 'Advances in Intelligent Data Analysis XIV'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Data Analytics and Optimisation for Assessing a Ride Sharing System
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    Chapter 2 Constraint-Based Querying for Bayesian Network Exploration
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    Chapter 3 Efficient Model Selection for Regularized Classification by Exploiting Unlabeled Data
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    Chapter 4 Segregation Discovery in a Social Network of Companies
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    Chapter 5 A First-Order-Logic Based Model for Grounded Language Learning
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    Chapter 6 A Parallel Distributed Processing Algorithm for Image Feature Extraction
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    Chapter 7 Modeling Concept Drift: A Probabilistic Graphical Model Based Approach
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    Chapter 8 Diversity-Driven Widening of Hierarchical Agglomerative Clustering
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    Chapter 9 Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering
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    Chapter 10 Time Series Classification with Representation Ensembles
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    Chapter 11 Simultaneous Clustering and Model Selection for Multinomial Distribution: A Comparative Study
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    Chapter 12 On Binary Reduction of Large-Scale Multiclass Classification Problems
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    Chapter 13 Probabilistic Active Learning in Datastreams
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    Chapter 14 Implicitly Constrained Semi-supervised Least Squares Classification
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    Chapter 15 Diagonal Co-clustering Algorithm for Document-Word Partitioning
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    Chapter 16 I-Louvain: An Attributed Graph Clustering Method
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    Chapter 17 Class-Based Outlier Detection: Staying Zombies or Awaiting for Resurrection?
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    Chapter 18 Using Metalearning for Prediction of Taxi Trip Duration Using Different Granularity Levels
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    Chapter 19 Using Entropy as a Measure of Acceptance for Multi-label Classification
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    Chapter 20 Investigation of Node Deletion Techniques for Clustering Applications of Growing Self Organizing Maps
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    Chapter 21 Exploratory Topic Modeling with Distributional Semantics
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    Chapter 22 Assigning Geo-relevance of Sentiments Mined from Location-Based Social Media Posts
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    Chapter 23 Continuous and Discrete Deep Classifiers for Data Integration
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    Chapter 24 A Bayesian Approach for Identifying Multivariate Differences Between Groups
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    Chapter 25 Automatically Discovering Offensive Patterns in Soccer Match Data
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    Chapter 26 Fast Algorithm Selection Using Learning Curves
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    Chapter 27 Optimally Weighted Cluster Kriging for Big Data Regression
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    Chapter 28 Slower Can Be Faster: The iRetis Incremental Model Tree Learner
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    Chapter 29 VoQs: A Web Application for Visualization of Questionnaire Surveys
Overall attention for this book and its chapters
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

2 tweeters

Readers on

33 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.
Advances in Intelligent Data Analysis XIV
Published by
Lecture notes in computer science, January 2015
DOI 10.1007/978-3-319-24465-5
978-3-31-924464-8, 978-3-31-924465-5

Fromont, Elisa, De Bie, Tijl, van Leeuwen, Matthijs


Elisa Fromont, Tijl De Bie, Matthijs van Leeuwen

Twitter Demographics

The data shown below were collected from the profiles of 2 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 3%
Unknown 32 97%
Readers by discipline Count As %
Computer Science 1 3%
Unknown 32 97%

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 08 November 2015.
All research outputs
of 9,678,133 outputs
Outputs from Lecture notes in computer science
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Outputs of similar age
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Outputs of similar age from Lecture notes in computer science
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Altmetric has tracked 9,678,133 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,061 research outputs from this source. They receive a mean Attention Score of 4.2. 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 343,001 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 51% of its contemporaries.
We're also able to compare this research output to 1,042 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.