Trends and Applications in Knowledge Discovery and Data Mining PAKDD 2018 Workshops BDASC BDM ML4Cyber PAISI DaMEMO Melbourne VIC Australia June 3 2018 Revised Selected Papers Mohadeseh Ganji 303004503X 9783030045036

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Product details:

• ISBN 10: 303004503X
• ISBN 13: 9783030045036
• Author: Mohadeseh Ganji

This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2018, held in conjunction with the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, in Melbourne, Australia, in June 2018. The 32 revised papers presented were carefully reviewed and selected from 46 submissions. The workshops affiliated with PAKDD 2018 include: Workshop on Big Data Analytics for Social Computing, BDASC, Australasian Workshop on Machine Learning for Cyber-security, ML4Cyber, Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining, BDM, Pacific Asia Workshop on Intelligence and Security Informatics, PAISI, and Workshop on Data Mining for Energy Modeling and Optimization, DaMEMO.

Table of contents:

Big Data Analytics for Social Computing (BDASC)

A Decision Tree Approach to Predicting Recidivism in Domestic Violence

Unsupervised Domain Adaptation Dictionary Learning for Visual Recognition

On the Large-Scale Transferability of Convolutional Neural Networks

Call Attention to Rumors: Deep Attention Based Recurrent Neural Networks for Early Rumor Detection

Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

Interesting Recommendations Based on Hierarchical Visualizations of Medical Data

Efficient Top K Temporal Spatial Keyword Search

HOC-Tree: A Novel Index for Efficient Spatio-Temporal Range Search

A Hybrid Index Model for Efficient Spatio-Temporal Search in HBase

Rumor Detection via Recurrent Neural Networks: A Case Study on Adaptivity with Varied Data Compositions

TwiTracker: Detecting and Extracting Events from Twitter for Entity Tracking

Australasian Workshop on Machine Learning for Cyber-Security (ML4Cyber)

Rapid Anomaly Detection Using Integrated Prudence Analysis (IPA)

A Differentially Private Method for Crowdsourcing Data Submission

An Anomaly Intrusion Detection System Using C5 Decision Tree Classifier

Deep Learning for Classifying Malicious Network Traffic

A Server Side Solution for Detecting WebInject: A Machine Learning Approach

A Novel LSTM-Based Daily Airline Demand Forecasting Method Using Vertical and Horizontal Time Series

A Transfer Metric Learning Method for Spammer Detection

Dynamic Whitelisting Using Locality Sensitive Hashing

Payload-Based Statistical Intrusion Detection for In-Vehicle Networks

Biologically-Inspired Techniques for Knowledge Discovery and Data Mining (BDM)

Discovering Strong Meta Association Rules Using Bees Swarm Optimization

ParallelPC: An R Package for Efficient Causal Exploration in Genomic Data

Citation Field Learning by RNN with Limited Training Data

Affine Transformation Capsule Net

A Novel Algorithm for Frequent Itemsets Mining in Transactional Databases

Rare-Events Classification: An Approach Based on Genetic Algorithm and Voronoi Tessellation

Particle Swarm Optimization-Based Weighted-Nadaraya-Watson Estimator

Pacific Asia Workshop on Intelligence and Security Informatics (PAISI)

A Parallel Implementation of Information Gain Using Hive in Conjunction with MapReduce for Continuous Features

Measuring Interpretability for Different Types of Machine Learning Models

In Search of Public Agenda with Text Mining: An Exploratory Study of Agenda Setting Dynamics Between the Traditional Media and Wikipedia

Modelling the Efficacy of Auto-Internet Warnings to Reduce Demand for Child Exploitation Materials

Data Mining for Energy Modeling and Optimization (DaMEMO)

Comparison and Sensitivity Analysis of Methods for Solar PV Power Prediction

An Improved PBIL Algorithm for Optimal Coalition Structure Generation of Smart Grids

Dam Inflow Time Series Regression Models Minimising Loss of Hydropower Opportunities

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