Search results for “Sequential Patterns

About 1 result in articles

Open Access Pub publishes peer-reviewed, free-to-read open-access articles. Showing articles matching Sequential Patterns — open any to read the full text, or download the PDF or XML.

1 article
Big Data Research Open Access

Mining Frequent Sequential Patterns

Mar 2021 DOI 10.14302/issn.2768-0207.jbr-21-3455
FAKIR YoussefCorresponding author Laboratory of Information Processing and Decision Support, University Sulan Moulay Slimane

In recent times, the urge to collect data and analyze it has grown. Time stamping a data set is an important part of the analysis and data mining as it can give information that is more useful. Different mining techniques have been designed for mining time-series data, sequential patterns for example seeks relationships between occurrences of sequential events and finds if there exist any specific order of the occurrences. Many Algorithms has been proposed to study this data type based on the apriori approach. In this paper we compare two basic sequential algorithms which are General Sequential algorithm (GSP) and Sequential PAttern Discovery using Equivalence classes (SPADE). These two algorithms are based on the Apriori algorithms. Experimental results have shown that SPADE consumes less time than GSP algorithm.

Frequently asked questions

Are these articles peer-reviewed?
Yes. Articles published at Open Access Pub go through single-blind peer review (double-blind on request) under an editorial board before publication.
Are the articles free to read?
Yes. Every article is open access — read the full text online for free and download the PDF or XML, with no paywall or subscription.
How do I cite an article?
Use the DOI shown on each result and on the article page; it is the permanent, citable link to the article.
How do I read or download an article?
Click "Read full text" to open the article HTML, or use the PDF / XML buttons on each card to download it.