XML Dataset and Benchmarks for Performance Testing of the CLS Labelling Scheme

Autor: Alhadi A. Klaib
Jazyk: Arabic<br />English
Rok vydání: 2021
Předmět:
Zdroj: مجلة العلوم البحتة والتطبيقية, Vol 20, Iss 2, Pp 12-15 (2021)
Druh dokumentu: article
ISSN: 2708-8251
2521-9200
DOI: 10.51984/jopas.v20i2.1243
Popis: Extensible Markup Language (XML) has become a significant technology for transferring data through the world of the Internet. XML labelling schemes are an essential technique used to handle XML data effectively. Labelling XML data is performed by assigning labels to all nodes in that XML document. CLS labelling scheme is a hybrid labelling scheme that was developed to address some limitations of indexing XML data. Moreover, datasets are used to test XML labelling schemes. There are many XML datasets available nowadays. Some of them are from real life datasets and others are from artificial datasets. These datasets and benchmarks are used for testing the XML labelling schemes. This paper discusses and considers these datasets and benchmarks and their specifications in order to determine the most appropriate one for testing the CLS labelling scheme. This research found out that the XMark benchmark is the most appropriate choice for the testing performance of the CLS labelling scheme.
Databáze: Directory of Open Access Journals