Publication detail

Generator of Synthetic Datasets for Hierarchical Sequential Pattern Mining Evaluation

ŠEBEK, M. ZENDULKA, J.

Original Title

Generator of Synthetic Datasets for Hierarchical Sequential Pattern Mining Evaluation

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

Evaluation is an important part of algorithm design. Algorithms are typically evaluated on real-world and synthetic datasets. Real-world datasets are appropriate for evaluation of algorithm properties in practice but it is difficult to change the dataset to have some particular statistics, e.g. number of input items. In contrast, generated synthetic dataset simply allows changing any of statistic property of the dataset with keeping all other statistic properties. In the paper, we present a procedure for generation of sequence databases with taxonomies for an evaluation of hierarchical sequential pattern mining algorithms.

Keywords

Sequence pattern mining, synthetic dataset generators, taxonomy

Authors

ŠEBEK, M.; ZENDULKA, J.

RIV year

2013

Released

5. 11. 2013

Publisher

The University of Technology Košice

Location

Košice

ISBN

978-80-8143-127-2

Book

Proceedings of the Twelfth International Conference on Informatics 2013

Pages from

289

Pages to

292

Pages count

4

URL

https://www.fit.vut.cz/research/publication/10435/

BibTex

@inproceedings{BUT103555,
  author="Michal {Šebek} and Jaroslav {Zendulka}",
  title="Generator of Synthetic Datasets for Hierarchical Sequential Pattern Mining Evaluation",
  booktitle="Proceedings of the Twelfth International Conference on Informatics 2013",
  year="2013",
  pages="289--292",
  publisher="The University of Technology Košice",
  address="Košice",
  isbn="978-80-8143-127-2",
  url="https://www.fit.vut.cz/research/publication/10435/"
}