An Algorithm to Mine Normalized Weighted Sequential Patterns Using a Prefix-projected Database

Autor:	Duong, Tran Huy, Thi, Vu Duc, Demetrovics, Janos
Rok vydání:	2016
Předmět:	Sequential Patterns Weighted Data Mining Frequent Sequential Patterns
Zdroj:	Serdica Journal of Computing. 9:105-122
ISSN:	1314-7897 1312-6555
Popis:	Sequential pattern mining is an important subject in data mining with broad applications in many different areas. However, previous sequential mining algorithms mostly aimed to calculate the number of occurrences (the support) without regard to the degree of importance of different data items. In this paper, we propose to explore the search space of subsequences with normalized weights. We are not only interested in the numberof occurrences of the sequences (supports of sequences), but also concernedabout importance of sequences (weights). When generating subsequencecandidates we use both the support and the weight of the candidates whilemaintaining the downward closure property of these patterns which allowsto accelerate the process of candidate generation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9c95b03c8765752906605c5add15b94 https://doi.org/10.55630/sjc.2015.9.105-122 Zobrazit plný text záznamu