Novel database design for extreme scale corpus analysis

Coole, Matthew and Rayson, Paul and Mariani, John (2021) Novel database design for extreme scale corpus analysis. PhD thesis, Lancaster University.

[thumbnail of 2021CoolePhD]
Text (2021CoolePhD)
2021coolephd.pdf - Published Version
Available under License Creative Commons Attribution.

Download (1MB)


This thesis presents the patterns and methods uncovered in the development of a new scalable corpus database management system, LexiDB, which can handle the ever-growing size of modern corpus datasets. Initially, an exploration of existing corpus data systems is conducted which examines their usage in corpus linguistics as well as their underlying architectures. From this survey, it is identified that existing systems are designed primarily to be vertically scalable (i.e. scalable through the usage of bigger, better and faster hardware). This motivates a wider examination of modern distributable database management systems and information retrieval techniques used for indexing and retrieval. These techniques are modified and adapted into an architecture that can be horizontally scaled to handle ever bigger corpora. Based on this architecture several new methods for querying and retrieval that improve upon existing techniques are proposed as modern approaches to query extremely large annotated text collections for corpus analysis. The effectiveness of these techniques and the scalability of the architecture is evaluated where it is demonstrated that the architecture is comparably scalable to two modern No-SQL database management systems and outperforms existing corpus data systems in token level pattern querying whilst still supporting character level pattern matching.

Item Type:
Thesis (PhD)
ID Code:
Deposited By:
Deposited On:
15 Feb 2021 10:15
Last Modified:
16 Jul 2024 05:54