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ŠEBEK, M.; ZENDULKA, J.
Original Title
Generator of Synthetic Datasets for Hierarchical Sequential Pattern Mining Evaluation
English Title
Type
Paper in proceedings outside WoS and Scopus
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.
English abstract
Keywords
Sequence pattern mining, synthetic dataset generators, taxonomy
Key words in English
Authors
RIV year
2014
Released
05.11.2013
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/" }
Documents
informatics-generator_draft