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FOURNIER-VIGER, P. GOMARIZ, A. ŠEBEK, M. HLOSTA, M.
Originální název
VGEN: Fast Vertical Mining of Sequential Generator Patterns
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Sequential pattern mining is a popular data mining task with wide applications. However, the set of all sequential patterns can be very large. To discover fewer but more representative patterns, several compact representations of sequential patterns have been studied. The set of sequential generatorsis one the most popular representations. It was shown to provide higher accuracy for classification than using all or only closed sequential patterns. Furthermore, mining generators is a key step in several other data mining tasks such as sequential rule generation. However, mining generators is computationally expensive. To address this issue, we propose a novel mining algorithm namedVGEN (Vertical sequential GENerator miner). An experimental study on five real datasets shows that VGEN is up to two orders of magnitude faster than the state-of-the-art algorithms for sequential generator mining.
Klíčová slova
sequential patterns, generators, vertical mining, candidate pruning
Autoři
FOURNIER-VIGER, P.; GOMARIZ, A.; ŠEBEK, M.; HLOSTA, M.
Rok RIV
2014
Vydáno
2. 9. 2014
Nakladatel
Springer Verlag
Místo
Munich
ISBN
978-3-319-10159-0
Kniha
Data Warehousing and Knowledge Discovery
Strany od
476
Strany do
488
Strany počet
12
URL
http://dx.doi.org/10.1007/978-3-319-10160-6_42
BibTex
@inproceedings{BUT111554, author="Philippe {Fournier-Viger} and Antonio {Gomariz} and Michal {Šebek} and Martin {Hlosta}", title="VGEN: Fast Vertical Mining of Sequential Generator Patterns", booktitle="Data Warehousing and Knowledge Discovery", year="2014", pages="476--488", publisher="Springer Verlag", address="Munich", doi="10.1007/978-3-319-10160-6\{_}42", isbn="978-3-319-10159-0", url="http://dx.doi.org/10.1007/978-3-319-10160-6_42" }