- 80 pages
- English
- PDF
- Available on iOS & Android
Label Hierarchy Inference in Property Graph Databases
About this book
Bachelor Thesis from the year 2020 in the subject Computer Science - Miscellaneous, grade: 1.1, University of Constance, language: English, abstract: A lot of data contains implicit hierarchical structures, e.g. type hierarchies. The property graph model – among others employed in some graph databases – provides no tools to capture those internally.In this thesis we derive such hierarchies automatically. First a survey is conducted to find the most promising approaches that cluster a data set hierarchically. In the next step various features and vectors thereof are experimented with to extend the methodology to graphs, capturing the structure as well as possible.We found that there is not one specific feature vector that works well for all data sets and forms of representation in a graph, but rather needs to be constructed adaptive, depending on the way data is modelled. Finally, some extensions of a specific algorithm that was used during experimentation – namely Cobweb – are discussed as well as the use case of cardinality estimation in property graph databases, leveraging the hierarchy as an associative multi-level histogram.
Frequently asked questions
- Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
- Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.