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Machine Learning and Knowledge Discovery in Databases

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Cover of 'Machine Learning and Knowledge Discovery in Databases'

Table of Contents

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    Book Overview
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    Chapter 1 Concentration Free Outlier Detection
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    Chapter 2 Efficient Top Rank Optimization with Gradient Boosting for Supervised Anomaly Detection
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    Chapter 3 Robust, Deep and Inductive Anomaly Detection
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    Chapter 4 Sentiment Informed Cyberbullying Detection in Social Media
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    Chapter 5 zooRank: Ranking Suspicious Entities in Time-Evolving Tensors
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    Chapter 6 Alternative Semantic Representations for Zero-Shot Human Action Recognition
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    Chapter 7 Early Active Learning with Pairwise Constraint for Person Re-identification
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    Chapter 8 Guiding InfoGAN with Semi-supervision
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    Chapter 9 Scatteract: Automated Extraction of Data from Scatter Plots
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    Chapter 10 Unsupervised Diverse Colorization via Generative Adversarial Networks
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    Chapter 11 Dynamic Ensemble Selection with Probabilistic Classifier Chains
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    Chapter 12 Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks
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    Chapter 13 Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks
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    Chapter 14 Deep Discrete Hashing with Self-supervised Pairwise Labels
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    Chapter 15 Including Multi-feature Interactions and Redundancy for Feature Ranking in Mixed Datasets
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    Chapter 16 Non-redundant Spectral Dimensionality Reduction
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    Chapter 17 Rethinking Unsupervised Feature Selection: From Pseudo Labels to Pseudo Must-Links
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    Chapter 18 SetExpan: Corpus-Based Set Expansion via Context Feature Selection and Rank Ensemble
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    Chapter 19 Bayesian Nonlinear Support Vector Machines for Big Data
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    Chapter 20 Entropic Trace Estimates for Log Determinants
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    Chapter 21 Fair Kernel Learning
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    Chapter 22 GaKCo: A Fast Gapped k-mer String Kernel Using Counting
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    Chapter 23 Graph Enhanced Memory Networks for Sentiment Analysis
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    Chapter 24 Kernel Sequential Monte Carlo
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    Chapter 25 Learning Łukasiewicz Logic Fragments by Quadratic Programming
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    Chapter 26 Nyström Sketches
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    Chapter 27 Crossprop: Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks
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    Chapter 28 Distributed Stochastic Optimization of Regularized Risk via Saddle-Point Problem
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    Chapter 29 Speeding up Hyper-parameter Optimization by Extrapolation of Learning Curves Using Previous Builds
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    Chapter 30 Thompson Sampling for Optimizing Stochastic Local Search
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    Chapter 31 Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation
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    Chapter 32 Content-Based Social Recommendation with Poisson Matrix Factorization
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    Chapter 33 C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization
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    Chapter 34 Feature Extraction for Incomplete Data via Low-rank Tucker Decomposition
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    Chapter 35 Structurally Regularized Non-negative Tensor Factorization for Spatio-Temporal Pattern Discoveries
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    Chapter 36 Attributed Graph Clustering with Unimodal Normalized Cut
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    Chapter 37 K-Clique-Graphs for Dense Subgraph Discovery
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    Chapter 38 Learning and Scaling Directed Networks via Graph Embedding
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    Chapter 39 Local Lanczos Spectral Approximation for Community Detection
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    Chapter 40 Regularizing Knowledge Graph Embeddings via Equivalence and Inversion Axioms
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    Chapter 41 Survival Factorization on Diffusion Networks
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    Chapter 42 The Network-Untangling Problem: From Interactions to Activity Timelines
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    Chapter 43 TransT: Type-Based Multiple Embedding Representations for Knowledge Graph Completion
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    Chapter 44 A Network Architecture for Multi-Multi-Instance Learning
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    Chapter 45 Con-S2V: A Generic Framework for Incorporating Extra-Sentential Context into Sen2Vec
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    Chapter 46 Deep Over-sampling Framework for Classifying Imbalanced Data
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    Chapter 47 FCNN: Fourier Convolutional Neural Networks
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    Chapter 48 Joint User Modeling Across Aligned Heterogeneous Sites Using Neural Networks
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    Chapter 49 Sequence Generation with Target Attention
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    Chapter 50 Wikipedia Vandal Early Detection: From User Behavior to User Embedding
Attention for Chapter 4: Sentiment Informed Cyberbullying Detection in Social Media
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Chapter title
Sentiment Informed Cyberbullying Detection in Social Media
Chapter number 4
Book title
Machine Learning and Knowledge Discovery in Databases
Published by
Springer, Cham, September 2017
DOI 10.1007/978-3-319-71249-9_4
Book ISBNs
978-3-31-971248-2, 978-3-31-971249-9
Authors

Harsh Dani, Jundong Li, Huan Liu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 99 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 20%
Student > Ph. D. Student 16 16%
Student > Bachelor 13 13%
Researcher 7 7%
Other 5 5%
Other 9 9%
Unknown 29 29%
Readers by discipline Count As %
Computer Science 49 49%
Engineering 4 4%
Social Sciences 3 3%
Psychology 2 2%
Decision Sciences 1 1%
Other 3 3%
Unknown 37 37%