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Trends and Applications in Knowledge Discovery and Data Mining : PAKDD 2017 Workshops, MLSDA, BDM, DM-BPM Jeju, South Korea, May 23, 2017, Revised Selected Papers / edited by U Kang, Ee-Peng Lim, Jeffrey Xu Yu, Yang-Sae Moon.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Kang, U., Editor.
Lim, Ee-Peng, Editor.
Yu, Jeffrey Xu, Editor.
Moon, Yang-Sae., Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 10526
Lecture Notes in Artificial Intelligence, 2945-9141 ; 10526
Language:
English
Subjects (All):
Artificial intelligence.
Data mining.
Medical informatics.
Information storage and retrieval systems.
Application software.
Computer science.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Health Informatics.
Information Storage and Retrieval.
Computer and Information Systems Applications.
Theory of Computation.
Local Subjects:
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Health Informatics.
Information Storage and Retrieval.
Computer and Information Systems Applications.
Theory of Computation.
Physical Description:
1 online resource (XIV, 203 pages) : 80 illustrations
Edition:
1st ed. 2017.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2017.
System Details:
text file PDF
Summary:
This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2017, held in conjunction with PAKDD, the 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining in May 2017 in Jeju, South Korea. The 17 revised papers presented were carefully reviewed and selected from 38 submissions. The workshops affiliated with PAKDD 2017 include: Workshop on Machine Learning for Sensory Data Analysis (MLSDA), Workshop on Biologically Inspired Data Mining Techniques (BDM), Pacific Asia Workshop on Intelligence and Security Informatics (PAISI), and Workshop on Data Mining in Business Process Management (DM-BPM).
Contents:
Early Classification of Multivariate Time Series on Distributed and In-Memory Platforms
Behavior Classification of Dairy Cows fitted with GPS collars
Dynamic Real-time Segmentation and Recongnition of Activities using a Multi-feature Windowing Approach
Feature Extraction from EEG data for a P300 Based Brain-computer Interface
Thermal Stratification Prediction at Lake Trevallyn
Development of a Software Vulnerability Prediction Web Service based on Artificial Neural Networks
Diversification Heuristics in Bees Swarm Optimization for Association Rules Mining
Improved CFDP Algorithms Based on Shared Nearest Neighbors and Transitive Closure
CNN-based Sequence Labeling for Fine-grained Opinion Mining of Microblogs
A Genetic Algorithm for Interpretable Model Extraction from Decision Tree Ensembles
Self-Adaptive Weighted Extreme Learning Machine for Imbalanced Classification Problems
Estimating Word Probabilities with Neural Networks in Latent Dirichlet Allocation
GA-Apriori: Combining Apriori Heuristic and Genetic Algorithms for Solving the Frequent Itemsets Mining Problem
Shelf Time Analysis in CTP Insurance Claims Processing
Automated Product-Attribute Mapping
A Novel Extreme Learning Machine-based Classification Algorithm for Uncertain Data
SPGLAD: A Self-Paced Learning-based Crowdsourcing Classification Model.
Other Format:
Printed edition:
ISBN:
978-3-319-67274-8
9783319672748
Access Restriction:
Restricted for use by site license.

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