Database Systems for Advanced Applications - Info and Reading Options
24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22–25, 2019, Proceedings, Part I
By Guoliang Li, Jun Yang, Joao Gama, Juggapong Natwichai and Yongxin Tong

"Database Systems for Advanced Applications" is published by Springer in Apr 25, 2019 - Cham and it has 841 pages.
“Database Systems for Advanced Applications” Metadata:
- Title: ➤ Database Systems for Advanced Applications
- Authors: Guoliang LiJun YangJoao GamaJuggapong NatwichaiYongxin Tong
- Number of Pages: 841
- Publisher: Springer
- Publish Date: Apr 25, 2019
- Publish Location: Cham
Edition Specifications:
- Format: paperback
Edition Identifiers:
- The Open Library ID: OL28184663M - OL20819142W
- ISBN-13: 9783030185756 - 9783030185763
- ISBN-10: 3030185753
- All ISBNs: 3030185753 - 9783030185756 - 9783030185763
AI-generated Review of “Database Systems for Advanced Applications”:
"Database Systems for Advanced Applications" Description:
Open Data:
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Big Data -- Accelerating Real-Time Tracking Applications over Big Data Stream with Constrained Space -- 1 Introduction -- 2 Approach Overview -- 2.1 Problem Statement -- 2.2 Design Principle -- 3 Approach Design -- 3.1 Software Architecture -- 3.2 Composed Sampling Strategies -- 3.3 Compression -- 4 Analysis -- 5 Experimental Evaluation -- 6 Related Work -- 7 Conclusion -- References -- A Frequency Scaling Based Performance Indicator Framework for Big Data Systems -- 1 Introduction -- 2 Related Work -- 3 Methodology for Building a Comparable Performance Indicator Framework -- 3.1 Problem Formulization -- 3.2 Performance Indicator Definition -- 4 Experimental Method -- 4.1 Cluster Setup -- 4.2 Running Mode -- 5 Experimental Results and Analysis -- 5.1 CPU Impact Analysis -- 5.2 Memory Impact Analysis -- 5.3 Disk Impact Analysis -- 5.4 Network Impact Analysis -- 5.5 Inaccuracy of Time Blocked White-Box Method -- 6 Discussion -- 7 Summary -- References -- A Time-Series Sockpuppet Detection Method for Dynamic Social Relationships -- 1 Introduction -- 2 Related Work -- 2.1 Verbal Features -- 2.2 Non-verbal Behavior -- 2.3 Network Structure -- 3 Time-Series Social Relationship -- 4 Sockpuppet Detection Method for Dynamic Social Relationships -- 4.1 Graph Construction -- 4.2 Interaction Graph with Time Series -- 4.3 Graph Similarity with Dynamic Social Relationship -- 4.4 Efficiency -- 5 Experiment and Results -- 5.1 Data Collection and Analysis -- 5.2 Experimental Design -- 5.3 Performance Evaluation Comparison -- 5.4 Parameter Analysis -- 5.5 Literature Comparison -- 6 Conclusion -- References -- Accelerating Hybrid Transactional/Analytical Processing Using Consistent Dual-Snapshot -- 1 Introduction -- 1.1 true-HTAP -- 1.2 Loose-Form HTAP -- 1.3 Motivation
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