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Discovery Science

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Cover of 'Discovery Science'

Table of Contents

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    Book Overview
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    Chapter 1 Explaining Mixture Models through Semantic Pattern Mining and Banded Matrix Visualization
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    Chapter 2 Big Data Analysis of StockTwits to Predict Sentiments in the Stock Market
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    Chapter 3 Synthetic Sequence Generator for Recommender Systems – Memory Biased Random Walk on a Sequence Multilayer Network
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    Chapter 4 Predicting Sepsis Severity from Limited Temporal Observations
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    Chapter 5 Completion Time and Next Activity Prediction of Processes Using Sequential Pattern Mining
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    Chapter 6 Antipattern Discovery in Ethiopian Bagana Songs
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    Chapter 7 Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project
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    Chapter 8 Multilayer Clustering: A Discovery Experiment on Country Level Trading Data
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    Chapter 9 Medical Document Mining Combining Image Exploration and Text Characterization
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    Chapter 10 Mining Cohesive Itemsets in Graphs
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    Chapter 11 Mining Rank Data
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    Chapter 12 Link Prediction on the Semantic MEDLINE Network
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    Chapter 13 Medical Image Retrieval Using Multimodal Data
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    Chapter 14 Fast Computation of the Tree Edit Distance between Unordered Trees Using IP Solvers
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    Chapter 15 Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency
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    Chapter 16 Incremental Learning with Social Media Data to Predict Near Real-Time Events
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    Chapter 17 Stacking Label Features for Learning Multilabel Rules
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    Chapter 18 Selective Forgetting for Incremental Matrix Factorization in Recommender Systems
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    Chapter 19 Providing Concise Database Covers Instantly by Recursive Tile Sampling
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    Chapter 20 Resampling-Based Framework for Estimating Node Centrality of Large Social Network
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    Chapter 21 Detecting Maximum k-Plex with Iterative Proper ℓ-Plex Search
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    Chapter 22 Exploiting Bhattacharyya Similarity Measure to Diminish User Cold-Start Problem in Sparse Data
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    Chapter 23 Failure Prediction – An Application in the Railway Industry
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    Chapter 24 Wind Power Forecasting Using Time Series Cluster Analysis
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    Chapter 25 Feature Selection in Hierarchical Feature Spaces
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    Chapter 26 Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology
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    Chapter 27 An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths
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    Chapter 28 Algorithm Selection on Data Streams
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    Chapter 29 Sparse Coding for Key Node Selection over Networks
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    Chapter 30 Variational Dependent Multi-output Gaussian Process Dynamical Systems
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    Chapter 31 Erratum: Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project
Attention for Chapter 7: Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project
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Chapter title
Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project
Chapter number 7
Book title
Discovery Science
Published in
Lecture notes in computer science, January 2014
DOI 10.1007/978-3-319-11812-3_7
Book ISBNs
978-3-31-911811-6, 978-3-31-911812-3
Authors

Tal Galili, Alexis Mitelpunkt, Netta Shachar, Mira Marcus-Kalish, Yoav Benjamini, Galili, Tal, Mitelpunkt, Alexis, Shachar, Netta, Marcus-Kalish, Mira, Benjamini, Yoav

Editors

Sašo Džeroski, Panče Panov, Dragi Kocev, Ljupčo Todorovski

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 35%
Researcher 4 24%
Student > Master 2 12%
Other 1 6%
Lecturer > Senior Lecturer 1 6%
Other 0 0%
Unknown 3 18%
Readers by discipline Count As %
Computer Science 4 24%
Neuroscience 3 18%
Medicine and Dentistry 2 12%
Social Sciences 1 6%
Mathematics 1 6%
Other 2 12%
Unknown 4 24%