Big data analytics and knowledge discovery : 22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14-17, 2020, Proceedings

Bibliographische Detailangaben

Titel
Big data analytics and knowledge discovery 22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14-17, 2020, Proceedings
verantwortlich
Song, Min (Computer scientist); Song, Il-Yeol.; Kotsis, Gabriele; Tjoa, A Min.; Khalil, Ismail; DaWaK (Conference) (22nd : 2020 : Online)
Schriftenreihe
Lecture Notes in Computer Science Ser. ; ; v.12393
veröffentlicht
Cham, Switzerland: Springer, [2020]
Erscheinungsjahr
2020
Teil von
Lecture notes in computer science ; ; 12393.
Medientyp
E-Book
Datenquelle
British National Bibliography
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Inhaltsangabe:
  • Intro
  • Preface
  • Organization
  • Contents
  • Position Paper
  • Analyzing the Research Landscape of DaWaK Papers from 1999 to 2019
  • 1 Introduction
  • 2 Experiment Design
  • 2.1 Data Collection
  • 2.2 Analysis Methods
  • 3 Results
  • 3.1 Co-words Map Analysis
  • 3.2 Topic Analysis
  • 3.3 Topic Trends Analysis
  • 3.4 DaWaK Research Paper Metrics
  • 4 Discussion and Conclusion
  • References
  • Applications
  • DHE2: Distributed Hybrid Evolution Engine for Performance Optimizations of Computationally Intensive Applications
  • 1 Introduction
  • 2 Related Work
  • 3 Methodology
  • 3.1 The Proposed Hybrid Evolutionary Algorithms
  • 3.2 Algorithm. Avoiding Local Optimum for Clustering
  • 4 Distributed Hybrid Evolution Engine Architecture
  • 5 Result Analysis
  • 6 Conclusions and Future Work
  • References
  • Grand Reports: A Tool for Generalizing Association Rule Mining to Numeric Target Values
  • 1 Introduction
  • 2 Grand Reports
  • 3 Association Rule Mining (ARM)
  • 4 The Proposed Tool
  • 4.1 Development and Functionalities
  • 4.2 Comparison and Advantages
  • 5 Conclusion
  • References
  • Expected vs. Unexpected: Selecting Right Measures of Interestingness
  • 1 Introduction
  • 2 Expectedness and Unexpectedness in ARM
  • 2.1 Objective Measures of Interestingness for Expected Association Rules
  • 2.2 Subjective Measures of Interestingness for Unexpected Association Rules
  • 2.3 Semantic Measures of Interestingness
  • 3 Properties for Selecting Objective Measures of Interestingness
  • 3.1 Towards Selecting Optimal Measures of Interestingness
  • 4 Conclusion
  • References
  • SONDER: A Data-Driven Methodology for Designing Net-Zero Energypg Public Buildings
  • 1 Introduction
  • 2 SONDER Methodology for Designing nZeB Solutions
  • 3 SONDER and ML as a Service for nZEBs
  • 4 Conclusion
  • References
  • Reverse Engineering Approach for NoSQL Databases
  • 1 Introduction
  • 2 Related Work
  • 3 Reverse Engineering Process
  • 3.1 Source: Physical Model
  • 3.2 Target: Conceptual Model
  • 3.3 Transformation Algorithms
  • 4 Experiments
  • 4.1 Implantation of the ToConceptualModel Process
  • 4.2 Comparison
  • 5 Conclusion and Future Work
  • References
  • Big Data/Data Lake
  • handle
  • A Generic Metadata Model for Data Lakes
  • 1 Introduction
  • 2 Related Work: Discussion of Existent Metadata Models
  • 2.1 Assessing the Basis of Existent Models
  • 2.2 Metadata Management Use Case for Model Evaluation
  • 2.3 Assessing the Generic Extent of the Existent Models
  • 3 Requirements for a Generic Metadata Model
  • 4 handle
  • A Generic Metadata Model
  • 5 handle Assessment
  • 5.1 handle Demonstration on Access-Use-Case
  • 5.2 Prototypical Implementation
  • 5.3 Fulfillment of Requirements
  • 5.4 Comparison to Existent Models
  • 6 Conclusion
  • References
  • Data Mining
  • A SAT-Based Approach for Mining High Utility Itemsets from Transaction Databases
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 High Utility Itemset Mining