Accepted author manuscript, 202 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version, 263 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Licence: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - LexiDB: Patterns & Methods for Corpus Linguistic Database Management
AU - Coole, Matthew
AU - Rayson, Paul
AU - Mariani, John
PY - 2020/5/11
Y1 - 2020/5/11
N2 - LexiDB is a tool for storing, managing and querying corpus data. In contrast to other database management systems (DBMSs), itis designed specifically for text corpora. It improves on other corpus management systems (CMSs) because data can be added anddeleted from corpora on the fly with the ability to add live data to existing corpora. LexiDB sits between these two categories ofDBMSs and CMSs, more specialised to language data than a general-purpose DBMS but more flexible than a traditional static corpusmanagement system. Previous work has demonstrated the scalability of LexiDB in response to the growing need to be able to scale outfor ever-growing corpus datasets. Here, we present the patterns and methods developed in LexiDB for storage, retrieval and querying ofmulti-level annotated corpus data. These techniques are evaluated and compared to an existing CMS (Corpus Workbench CWB - CQP)and indexer (Lucene). We find that LexiDB consistently outperforms existing tools for corpus queries. This is particularly apparent withlarge corpora and when handling queries with large result sets.
AB - LexiDB is a tool for storing, managing and querying corpus data. In contrast to other database management systems (DBMSs), itis designed specifically for text corpora. It improves on other corpus management systems (CMSs) because data can be added anddeleted from corpora on the fly with the ability to add live data to existing corpora. LexiDB sits between these two categories ofDBMSs and CMSs, more specialised to language data than a general-purpose DBMS but more flexible than a traditional static corpusmanagement system. Previous work has demonstrated the scalability of LexiDB in response to the growing need to be able to scale outfor ever-growing corpus datasets. Here, we present the patterns and methods developed in LexiDB for storage, retrieval and querying ofmulti-level annotated corpus data. These techniques are evaluated and compared to an existing CMS (Corpus Workbench CWB - CQP)and indexer (Lucene). We find that LexiDB consistently outperforms existing tools for corpus queries. This is particularly apparent withlarge corpora and when handling queries with large result sets.
M3 - Conference contribution/Paper
SN - 9791095546344
SP - 3128
EP - 3135
BT - Proceedings of The 12th Language Resources and Evaluation Conference
PB - European Language Resources Association (ELRA)
CY - Paris
ER -