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
- ; ; ; ; ;
- Schriftenreihe
- Lecture Notes in Computer Science Ser. ; ; v.12393
- veröffentlicht
- 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