An efficient method for mining sequential patterns with indices

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63549719" target="_blank" >RIV/70883521:28140/22:63549719 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0950705121010832" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0950705121010832</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.knosys.2021.107946" target="_blank" >10.1016/j.knosys.2021.107946</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An efficient method for mining sequential patterns with indices

Popis výsledku v původním jazyce

In recent years, mining informative data and discovering hidden information have become increasingly in demand. One of the popular means to achieve this is sequential pattern mining, which is to find informative patterns stored in databases. Its applications cover different areas and many methods have been proposed. Recently, pseudo-IDLists were proposed to improve both runtime and memory usage in the mining process. However, the idea cannot be directly used for sequential pattern mining as it only works on clickstream patterns, a more distinct type of sequential pattern. We propose adaptations and changes to the original idea to introduce SUI (Sequential pattern mining Using Indices). Comparing SUI with two other state-of-the-art algorithms on six test databases, we show that SUI has effective and efficient performance and memory usage.

Název v anglickém jazyce

An efficient method for mining sequential patterns with indices

Popis výsledku anglicky

In recent years, mining informative data and discovering hidden information have become increasingly in demand. One of the popular means to achieve this is sequential pattern mining, which is to find informative patterns stored in databases. Its applications cover different areas and many methods have been proposed. Recently, pseudo-IDLists were proposed to improve both runtime and memory usage in the mining process. However, the idea cannot be directly used for sequential pattern mining as it only works on clickstream patterns, a more distinct type of sequential pattern. We propose adaptations and changes to the original idea to introduce SUI (Sequential pattern mining Using Indices). Comparing SUI with two other state-of-the-art algorithms on six test databases, we show that SUI has effective and efficient performance and memory usage.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Knowledge-Based Systems

ISSN

0950-7051

e-ISSN

1872-7409

Svazek periodika

239

Číslo periodika v rámci svazku

Neuveden

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

12

Strana od-do

1-12

Kód UT WoS článku

000788633300001

EID výsledku v databázi Scopus

2-s2.0-85122511875