Pivot graph computation

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Table of contents

1 Introduction 
1.1 Modeling Science Evolution
1.2 The EPIQUE project
1.3 Research Challenges
1.3.1 Challenge 1: Scalability
1.3.2 Challenge 2: Tuning and Quality
1.3.3 Challenge 3: Interactive Exploration and Analysis
1.4 Contributions and thesis outline
1.4.1 Topic Evolution Framework
1.4.2 Pivot graph computation
1.4.3 Experimental Evaluation
1.5 List of Publications
2 Related Work 
2.1 Topic Modeling
2.1.1 Topic Modeling Approaches
2.1.2 Latent Topic Models
2.1.3 Dynamic Topic Modeling
2.2 Topic Evolution Models
2.2.1 Topic Trend Analysis
2.2.2 Topic Evolution Networks
3 Phylomemy Generation 
3.1 Phylomemy Generation Workflow
3.1.1 Data Preprocessing
3.1.2 Corpus Periodization
3.1.3 Topic Extraction
3.1.4 Topic Evolution Alignment
3.2 Topic Extraction
3.2.1 Diversity Estimation
3.2.2 Experimental Evaluation
3.3 Topic Alignment
3.3.1 Full Matrix Alignment Computation
3.3.2 Nearest-Neighbor Alignment Computation
4 Pivot Graph Model and Query Language 
4.1 Topic Evolution Model
4.2 Pivot Topic Graphs
4.3 Pivot Topic Functions
4.4 Pivot Topic Calculus
4.5 Pivot Topic Query Language
5 Pivot Graph Generation 
5.1 Relational Pivot Graph Computation
5.1.1 Baseline Join-based TC computation
5.1.2 Smart Join-based TC Computation
5.1.3 Incremental Join-based TC Computation
5.2 BSP-based Pivot Graph Computation
5.2.1 The Pregel operator
5.2.2 The Pregel operator in GraphX
5.2.3 Future Pivot Graph Generation with Pregel
5.3 Experiments
5.3.1 Comparison of Relational TC Computations
5.3.2 Parallelization and Scalability
5.3.3 Join-based versus Pregel-based TC Computation
5.3.4 Conclusion
6 Implementation and Prototype 
6.1 Pivot Graph Generation and Query Evaluation
6.1.1 Pivot Graph Computation with Spark
6.1.2 Topic Label Computation
6.1.3 Pivot Graph Metrics Computation
6.1.4 Pivot Query Evaluation
6.2 EPIQUE Prototype
6.2.1 Prototype Architecture
6.2.2 The Topic Evolution Graph Generator Notebook
6.2.3 The Topic Evolution Graph Explorator Notebook
6.2.4 Some Pivot Graph Examples
7 Conclusion and Future Work 
7.1 Main Contributions
7.1.1 Topic Evolution Network Computation
7.1.2 Pivot Graph Model and Query Language
7.1.3 Implementation and Optimization
7.2 Future Work
7.2.1 Generic Topic Evolution Workflow
7.2.2 Topic Evolution Model and Query Language

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