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Discovery Science

Overview of attention for book
Cover of 'Discovery Science'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 The CURE for Class Imbalance
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    Chapter 2 Mining a Maximum Weighted Set of Disjoint Submatrices
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    Chapter 3 Dataset Morphing to Analyze the Performance of Collaborative Filtering
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    Chapter 4 Construction of Histogram with Variable Bin-Width Based on Change Point Detection
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    Chapter 5 A Unified Approach to Biclustering Based on Formal Concept Analysis and Interval Pattern Structure
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    Chapter 6 A Sampling-Based Approach for Discovering Subspace Clusters
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    Chapter 7 Epistemic Uncertainty Sampling
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    Chapter 8 Utilizing Hierarchies in Tree-Based Online Structured Output Prediction
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    Chapter 9 On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics
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    Chapter 10 Hyperparameter Importance for Image Classification by Residual Neural Networks
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    Chapter 11 Cellular Traffic Prediction and Classification: A Comparative Evaluation of LSTM and ARIMA
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    Chapter 12 Main Factors Driving the Open Rate of Email Marketing Campaigns
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    Chapter 13 Enhancing BMI-Based Student Clustering by Considering Fitness as Key Attribute
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    Chapter 14 Deep Learning Does Not Generalize Well to Recognizing Cats and Dogs in Chinese Paintings
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    Chapter 15 Temporal Analysis of Adverse Weather Conditions Affecting Wheat Production in Finland
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    Chapter 16 Predicting Thermal Power Consumption of the Mars Express Satellite with Data Stream Mining
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    Chapter 17 Parameter-Less Tensor Co-clustering
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    Chapter 18 Deep Triplet-Driven Semi-supervised Embedding Clustering
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    Chapter 19 Neurodegenerative Disease Data Ontology
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    Chapter 20 Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification
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    Chapter 21 Symbolic Graph Embedding Using Frequent Pattern Mining
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    Chapter 22 Feature Selection for Analogy-Based Learning to Rank
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    Chapter 23 Ensemble-Based Feature Ranking for Semi-supervised Classification
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    Chapter 24 Variance-Based Feature Importance in Neural Networks
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    Chapter 25 A Density Estimation Approach for Detecting and Explaining Exceptional Values in Categorical Data
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    Chapter 26 A Framework for Human-Centered Exploration of Complex Event Log Graphs
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    Chapter 27 Sparse Robust Regression for Explaining Classifiers
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    Chapter 28 Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning
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    Chapter 29 Evolving Social Networks Analysis via Tensor Decompositions: From Global Event Detection Towards Local Pattern Discovery and Specification
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    Chapter 30 Efficient and Accurate Non-exhaustive Pattern-Based Change Detection in Dynamic Networks
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    Chapter 31 A Combinatorial Multi-Armed Bandit Based Method for Dynamic Consensus Community Detection in Temporal Networks
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    Chapter 32 Resampling-Based Framework for Unbiased Estimator of Node Centrality over Large Complex Network
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    Chapter 33 Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes
  35. Altmetric Badge
    Chapter 34 Ensemble Clustering for Novelty Detection in Data Streams
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    Chapter 35 Mining Patterns in Source Code Using Tree Mining Algorithms
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    Chapter 36 KnowBots: Discovering Relevant Patterns in Chatbot Dialogues
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    Chapter 37 Fast Distance-Based Anomaly Detection in Images Using an Inception-Like Autoencoder
  39. Altmetric Badge
    Chapter 38 Adaptive Long-Term Ensemble Learning from Multiple High-Dimensional Time-Series
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    Chapter 39 Fourier-Based Parametrization of Convolutional Neural Networks for Robust Time Series Forecasting
  41. Altmetric Badge
    Chapter 40 Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption
Attention for Chapter 21: Symbolic Graph Embedding Using Frequent Pattern Mining
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About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
14 Mendeley
Summary X Dimensions citations
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Chapter title
Symbolic Graph Embedding Using Frequent Pattern Mining
Chapter number 21
Book title
Discovery Science
Published in
arXiv, October 2019
DOI 10.1007/978-3-030-33778-0_21
Book ISBNs
978-3-03-033777-3, 978-3-03-033778-0
Authors

Blaž Škrlj, Nada Lavrač, Jan Kralj, Blaz Škrlj, Škrlj, Blaž, Lavrač, Nada, Kralj, Jan

View on publisher site
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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 14%
Student > Master 2 14%
Student > Bachelor 1 7%
Other 1 7%
Researcher 1 7%
Other 0 0%
Unknown 7 50%
Readers by discipline Count As %
Computer Science 5 36%
Linguistics 1 7%
Engineering 1 7%
Unknown 7 50%
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 31 October 2019.
All research outputs
#19,630,735
of 24,998,746 outputs
Outputs from arXiv
#470,695
of 1,020,408 outputs
Outputs of similar age
#264,205
of 369,636 outputs
Outputs of similar age from arXiv
#13,940
of 28,757 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,020,408 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 44th percentile – i.e., 44% 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 369,636 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28,757 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.

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