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Advances in Intelligent Data Analysis X

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Cover of 'Advances in Intelligent Data Analysis X'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Advances in Intelligent Data Analysis X
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    Chapter 2 Computational Sustainability
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    Chapter 3 Intelligent Data Analysis: Keeping Pace with Technological Advances
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    Chapter 4 Comparative Analysis of Power Consumption in University Buildings Using envSOM
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    Chapter 5 Context-Aware Collaborative Data Stream Mining in Ubiquitous Devices
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    Chapter 6 Advances in Intelligent Data Analysis X
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    Chapter 7 Mining Fault-Tolerant Item Sets Using Subset Size Occurrence Distributions
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    Chapter 8 Finding Ensembles of Neurons in Spike Trains by Non-linear Mapping and Statistical Testing
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    Chapter 9 Towards Automatic Pathway Generation from Biological Full-Text Publications
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    Chapter 10 Online Writing Data Representation: A Graph Theory Approach
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    Chapter 11 Online Evaluation of Email Streaming Classifiers Using GNUsmail
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    Chapter 12 The Dynamic Stage Bayesian Network: Identifying and Modelling Key Stages in a Temporal Process
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    Chapter 13 Mining Train Delays
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    Chapter 14 Robustness of Change Detection Algorithms
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    Chapter 15 GaMuSo: Graph Base Music Recommendation in a Social Bookmarking Service
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    Chapter 16 Resampling-Based Change Point Estimation
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    Chapter 17 Learning about the Learning Process
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    Chapter 18 Predicting Computer Performance Dynamics
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    Chapter 19 Prototype-Based Classification of Dissimilarity Data
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    Chapter 20 Automatic Layout Design Solution
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    Chapter 21 An Alternative to ROC and AUC Analysis of Classifiers
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    Chapter 22 The Algorithm APT to Classify in Concurrence of Latency and Drift
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    Chapter 23 Identification of Nuclear Magnetic Resonance Signals via Gaussian Mixture Decomposition
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    Chapter 24 Graphical Feature Selection for Multilabel Classification Tasks
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    Chapter 25 A Web2.0 Strategy for the Collaborative Analysis of Complex Bioimages
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    Chapter 26 Data Quality through Model Checking Techniques
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    Chapter 27 Generating Automated News to Explain the Meaning of Sensor Data
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    Chapter 28 Binding Statistical and Machine Learning Models for Short-Term Forecasting of Global Solar Radiation
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    Chapter 29 Advances in Intelligent Data Analysis X
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    Chapter 30 Advances in Intelligent Data Analysis X
  32. Altmetric Badge
    Chapter 31 Mining Sentiments from Songs Using Latent Dirichlet Allocation
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    Chapter 32 Analyzing Parliamentary Elections Based on Voting Advice Application Data
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    Chapter 33 Integrating Marine Species Biomass Data by Modelling Functional Knowledge
  35. Altmetric Badge
    Chapter 34 A Stylometric Study and Assessment of Machine Translators
  36. Altmetric Badge
    Chapter 35 Traffic Events Modeling for Structural Health Monitoring
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    Chapter 36 Advances in Intelligent Data Analysis X
  38. Altmetric Badge
    Chapter 37 iMMPC: A Local Search Approach for Incremental Bayesian Network Structure Learning
  39. Altmetric Badge
    Chapter 38 Analyzing Emotional Semantics of Abstract Art Using Low-Level Image Features
Attention for Chapter 32: Analyzing Parliamentary Elections Based on Voting Advice Application Data
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Chapter title
Analyzing Parliamentary Elections Based on Voting Advice Application Data
Chapter number 32
Book title
Advances in Intelligent Data Analysis X
Published in
Lecture notes in computer science, October 2011
DOI 10.1007/978-3-642-24800-9_32
Book ISBNs
978-3-64-224799-6, 978-3-64-224800-9
Authors

Jaakko Talonen, Mika Sulkava

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 50%
Student > Ph. D. Student 1 17%
Student > Master 1 17%
Unknown 1 17%
Readers by discipline Count As %
Social Sciences 3 50%
Earth and Planetary Sciences 1 17%
Engineering 1 17%
Unknown 1 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 November 2011.
All research outputs
#20,187,333
of 22,703,044 outputs
Outputs from Lecture notes in computer science
#6,982
of 8,124 outputs
Outputs of similar age
#129,320
of 141,020 outputs
Outputs of similar age from Lecture notes in computer science
#45
of 53 outputs
Altmetric has tracked 22,703,044 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,124 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 1st percentile – i.e., 1% 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 141,020 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.