Advances in Knowledge Discovery and Data Mining 22nd Pacific Asia Conference PAKDD 2018 Melbourne VIC Australia June 3 6 2018 Proceedings Part I 1st Edition by Dinh Phung,Vincent S Tseng,Geoffrey I Webb,Bao Ho,Mohadeseh Ganji,Lida Rashidi ISBN 3319930338 978-3319930336

Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part I 1st Edition by Dinh Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi – Ebook PDF Instant Download/Delivery: 3319930338, 978-3319930336

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Product details:

ISBN 10: 3319930338 

ISBN 13: 978-3319930336

Author: Dinh Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi

This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018.

The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications.

Table of contents: 

Part 1: Feature Learning and Data Mining Process
Chapter 1: High Utility Itemset Mining
Chapter 2: Record Linkage and Data Matching
Chapter 3: Feature Selection Techniques
Chapter 4: Dimensionality Reduction and Data Imputation
Chapter 5: Data Compression and Approximation Algorithms

Part 2: Community Detection and Network Science
Chapter 6: Community Detection Techniques
Chapter 7: Social Network and Trust Modeling

Part 3: Deep Learning Theory and Applications in KDD
Chapter 8: Deep Learning for Text and Sequences
Chapter 9: Neural Network-Based Data Imputation and Classification
Chapter 10: Deep Learning for Image and Object Recognition
Chapter 11: Deep Learning for Time Series and Data Augmentation
Chapter 12: Advanced Neural Network Models

Part 4: Clustering and Unsupervised Learning
Chapter 13: Density-Based Clustering
Chapter 14: Document and Graph-Based Clustering

Part 5: Privacy-Preserving and Security
Chapter 15: Privacy and Security in Data Mining

Part 6: Recommendation and Data Factorization
Chapter 16: Personalized and Context-Aware Recommendations

Part 7: Social Network, Ubiquitous Data, and Graph Mining
Chapter 17: Social Network Analysis and Influence Modeling
Chapter 18: Graph Mining and Prediction Models
Chapter 19: Advanced Network Science and Graph Analysis
Chapter 20: Real-World Applications of Social Network Mining

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Tags: Dinh Phung, Vincent S Tseng, Geoffrey I Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi, Advances in Knowledge, Discovery and Data Mining, 22nd Pacific Asia Conference