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Advances in Intelligent Data Analysis XV

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

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 DSCo-NG: A Practical Language Modeling Approach for Time Series Classification
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    Chapter 2 Ranking Accuracy for Logistic-GEE Models
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    Chapter 3 The Morality Machine: Tracking Moral Values in Tweets
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    Chapter 4 A Hybrid Approach for Probabilistic Relational Models Structure Learning
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    Chapter 5 On the Impact of Data Set Size in Transfer Learning Using Deep Neural Networks
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    Chapter 6 Obtaining Shape Descriptors from a Concave Hull-Based Clustering Algorithm
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    Chapter 7 Visual Perception of Discriminative Landmarks in Classified Time Series
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    Chapter 8 Spotting the Diffusion of New Psychoactive Substances over the Internet
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    Chapter 9 Feature Selection Issues in Long-Term Travel Time Prediction
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    Chapter 10 A Mean-Field Variational Bayesian Approach to Detecting Overlapping Communities with Inner Roles Using Poisson Link Generation
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    Chapter 11 Online Semi-supervised Learning for Multi-target Regression in Data Streams Using AMRules
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    Chapter 12 A Toolkit for Analysis of Deep Learning Experiments
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    Chapter 13 The Optimistic Method for Model Estimation
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    Chapter 14 Does Feature Selection Improve Classification? A Large Scale Experiment in OpenML
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    Chapter 15 Learning from the News: Predicting Entity Popularity on Twitter
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    Chapter 16 Multi-scale Kernel PCA and Its Application to Curvelet-Based Feature Extraction for Mammographic Mass Characterization
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    Chapter 17 Weakly-Supervised Symptom Recognition for Rare Diseases in Biomedical Text
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    Chapter 18 Estimating Sequence Similarity from Read Sets for Clustering Sequencing Data
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    Chapter 19 Widened Learning of Bayesian Network Classifiers
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    Chapter 20 Vote Buying Detection via Independent Component Analysis
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    Chapter 21 Unsupervised Relation Extraction in Specialized Corpora Using Sequence Mining
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    Chapter 22 A Framework for Interpolating Scattered Data Using Space-Filling Curves
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    Chapter 23 Privacy-Awareness of Distributed Data Clustering Algorithms Revisited
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    Chapter 24 Bi-stochastic Matrix Approximation Framework for Data Co-clustering
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    Chapter 25 Sequential Cost-Sensitive Feature Acquisition
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    Chapter 26 Explainable and Efficient Link Prediction in Real-World Network Data
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    Chapter 27 DGRMiner: Anomaly Detection and Explanation in Dynamic Graphs
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    Chapter 28 Similarity Based Hierarchical Clustering with an Application to Text Collections
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    Chapter 29 Determining Data Relevance Using Semantic Types and Graphical Interpretation Cues
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    Chapter 30 A First Step Toward Quantifying the Climate’s Information Production over the Last 68,000 Years
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    Chapter 31 HAUCA Curves for the Evaluation of Biomarker Pilot Studies with Small Sample Sizes and Large Numbers of Features
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    Chapter 32 Stability Evaluation of Event Detection Techniques for Twitter
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    Chapter 33 IDA 2016 Industrial Challenge: Using Machine Learning for Predicting Failures
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    Chapter 34 An Optimized k-NN Approach for Classification on Imbalanced Datasets with Missing Data
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    Chapter 35 Combining Boosted Trees with Metafeature Engineering for Predictive Maintenance
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    Chapter 36 Prediction of Failures in the Air Pressure System of Scania Trucks Using a Random Forest and Feature Engineering
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
4 news outlets
blogs
1 blog
twitter
4 tweeters

Readers on

mendeley
48 Mendeley
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Title
Advances in Intelligent Data Analysis XV
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-46349-0
ISBNs
978-3-31-946348-3, 978-3-31-946349-0
Editors

Henrik Boström, Arno Knobbe, Carlos Soares, Panagiotis Papapetrou

Twitter Demographics

The data shown below were collected from the profiles of 4 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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 23%
Student > Master 10 21%
Researcher 5 10%
Professor > Associate Professor 4 8%
Professor 2 4%
Other 9 19%
Unknown 7 15%
Readers by discipline Count As %
Computer Science 22 46%
Engineering 5 10%
Agricultural and Biological Sciences 4 8%
Decision Sciences 2 4%
Earth and Planetary Sciences 2 4%
Other 5 10%
Unknown 8 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 42. 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 31 May 2017.
All research outputs
#287,009
of 11,194,639 outputs
Outputs from Lecture notes in computer science
#62
of 7,165 outputs
Outputs of similar age
#15,057
of 263,812 outputs
Outputs of similar age from Lecture notes in computer science
#1
of 102 outputs
Altmetric has tracked 11,194,639 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,165 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 99% 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 263,812 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 102 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 99% of its contemporaries.