A novel sequential pattern mining algorithm for large scale data sequences

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dc.authorid0000-0002-4958-4575en_US
dc.authorscopusid55355863500en_US
dc.contributor.authorCan, Ali Burak
dc.contributor.authorUzun-Per, Meryem
dc.contributor.authorAktaş, Mehmet Sıddık
dc.date.accessioned2023-01-17T06:45:41Z
dc.date.available2023-01-17T06:45:41Z
dc.date.issued2022en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractSequential pattern mining algorithms are unsupervised machine learning algorithms that allow finding sequential patterns on data sequences that have been put together based on a particular order. These algorithms are mostly optimized for finding sequential data sequences containing more than one element. Hence, we argue that there is a need for algorithms that are particularly optimized for data sequences that contain only one element. Within the scope of this research, we study the design and development of a novel algorithm that is optimized for data sets containing data sequences with single elements and that can detect sequential patterns with high performance. The time and memory requirements of the proposed algorithm are examined experimentally. The results show that the proposed algorithm has low running times, while it has the same accuracy results as the algorithms in the similar category in the literature. The obtained results are promising.en_US
dc.identifier.citationCan, A. B., Uzun-Per, M. & Aktaş, M. S. (2022). A novel sequential pattern mining algorithm for large scale data sequences. Computational Science and Its Applications – ICCSA 2022 Workshops (pp. 698-708). Springer: Malaga, Spain. https://doi.org/10.1007/978-3-031-10536-4en_US
dc.identifier.doi10.1007/978-3-031-10536-4_46en_US
dc.identifier.endpage708en_US
dc.identifier.isbn9783031105357
dc.identifier.isbn9783031105364
dc.identifier.scopus2-s2.0-85135954552en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage698en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-10536-4_46
dc.identifier.urihttps://hdl.handle.net/20.500.13055/373
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorUzun-Per, Meryem
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofComputational Science and Its Applications – ICCSA 2022 Workshopsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSequential Pattern Miningen_US
dc.subjectGspen_US
dc.subjectPrefixspanen_US
dc.subjectLarge Scale Data Sequencesen_US
dc.subjectMapreduce Programming Modelen_US
dc.titleA novel sequential pattern mining algorithm for large scale data sequencesen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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