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Advances in Intelligent Data Analysis XI

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

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Over-Fitting in Model Selection and Its Avoidance
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    Chapter 2 Intelligent Data Analysis of Human Genetic Data
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    Chapter 3 Queries for Data Analysis
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    Chapter 4 Advances in Intelligent Data Analysis XI
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    Chapter 5 Weighting Features for Partition around Medoids Using the Minkowski Metric
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    Chapter 6 On Initializations for the Minkowski Weighted K-Means
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    Chapter 7 A Skew- t -Normal Multi-level Reduced-Rank Functional PCA Model for the Analysis of Replicated Genomics Time Course Data
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    Chapter 8 Methodological Foundation for Sign Language 3D Motion Trajectory Analysis
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    Chapter 9 Advances in Intelligent Data Analysis XI
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    Chapter 10 Online Techniques for Dealing with Concept Drift in Process Mining
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    Chapter 11 Advances in Intelligent Data Analysis XI
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    Chapter 12 Advances in Intelligent Data Analysis XI
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    Chapter 13 Discriminative Dimensionality Reduction Mappings
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    Chapter 14 Advances in Intelligent Data Analysis XI
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    Chapter 15 Curve Fitting for Short Time Series Data from High Throughput Experiments with Correction for Biological Variation
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    Chapter 16 Advances in Intelligent Data Analysis XI
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    Chapter 17 MCut: A Thresholding Strategy for Multi-label Classification
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    Chapter 18 Improving Tag Recommendation Using Few Associations
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    Chapter 19 Identifying Anomalous Social Contexts from Mobile Proximity Data Using Binomial Mixture Models
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    Chapter 20 Constrained Clustering Using SAT
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    Chapter 21 Advances in Intelligent Data Analysis XI
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    Chapter 22 Advances in Intelligent Data Analysis XI
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    Chapter 23 Analysis of Noisy Biosignals for Musical Performance
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    Chapter 24 Information Theoretic Approach to Improve Performance of Networked Control Systems
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    Chapter 25 Advances in Intelligent Data Analysis XI
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    Chapter 26 G e T_M ove : An Efficient and Unifying Spatio-temporal Pattern Mining Algorithm for Moving Objects
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    Chapter 27 Fuzzy Frequent Pattern Mining in Spike Trains
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    Chapter 28 Advances in Intelligent Data Analysis XI
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    Chapter 29 Advances in Intelligent Data Analysis XI
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    Chapter 30 Applying Piecewise Approximation in Perceptron Training of Conditional Random Fields
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    Chapter 31 Patch-Based Data Analysis Using Linear-Projection Diffusion
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    Chapter 32 Dictionary Construction for Patch-to-Tensor Embedding
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    Chapter 33 Where Are We Going? Predicting the Evolution of Individuals
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    Chapter 34 Use of General Purpose GPU Programming to Enhance the Classification of Leukaemia Blast Cells in Blood Smear Images
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    Chapter 35 Intelligent Data Analysis by a Home-Use Human Monitoring Robot
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    Chapter 36 Advances in Intelligent Data Analysis XI
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    Chapter 37 Engine Parameter Outlier Detection: Verification by Simulating PID Controllers Generated by Genetic Algorithm
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    Chapter 38 Unit Operational Pattern Analysis and Forecasting Using EMD and SSA for Industrial Systems
Attention for Chapter 18: Improving Tag Recommendation Using Few Associations
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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 (58th percentile)

Mentioned by

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3 X users

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5 Mendeley
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Chapter title
Improving Tag Recommendation Using Few Associations
Chapter number 18
Book title
Advances in Intelligent Data Analysis XI
Published in
Lecture notes in computer science, January 2012
DOI 10.1007/978-3-642-34156-4_18
Book ISBNs
978-3-64-234155-7, 978-3-64-234156-4
Authors

Matthijs van Leeuwen, Diyah Puspitaningrum, van Leeuwen, Matthijs, Puspitaningrum, Diyah

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 20%
Student > Bachelor 1 20%
Student > Ph. D. Student 1 20%
Student > Master 1 20%
Researcher 1 20%
Other 0 0%
Readers by discipline Count As %
Computer Science 3 60%
Psychology 1 20%
Unknown 1 20%
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 25 October 2012.
All research outputs
#13,023,610
of 22,684,168 outputs
Outputs from Lecture notes in computer science
#3,904
of 8,122 outputs
Outputs of similar age
#144,458
of 244,115 outputs
Outputs of similar age from Lecture notes in computer science
#202
of 490 outputs
Altmetric has tracked 22,684,168 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,122 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 51% 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 244,115 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 490 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 58% of its contemporaries.