Mining Frequent Sequential Patterns over Sequence Data Streams with a Gap-Constraint (순차 데이터 스트림에서 발생 간격 제한 조건을 활용한 빈발 순차 패턴 탐색)

장중혁

Mining Frequent Sequential Patterns over Sequence Data Streams with a Gap-Constraint

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2010, 15(9), pp.35-46
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

장중혁 ¹

¹대구대학교

Accredited

ABSTRACT

Sequential pattern mining is one of the essential data mining tasks, and it is widely used to analyze data generated in various application fields such as web-based applications, E-commerce, bioinformatics, and USN environments. Recently data generated in the application fields has been taking the form of continuous data streams rather than finite stored data sets. Considering the changes in the form of data, many researches have been actively performed to efficiently find sequential patterns over data streams. However, conventional researches focus on reducing processing time and memory usage in mining sequential patterns over a target data stream, so that a research on mining more interesting and useful sequential patterns that efficiently reflect the characteristics of the data stream has been attracting no attention. This paper proposes a mining method of sequential patterns over data streams with a gap constraint, which can help to find more interesting sequential patterns over the data streams. First, meanings of the gap for a sequential pattern and gap-constrained sequential patterns are defined, and subsequently a mining method for finding gap-constrained sequential patterns over a data stream is proposed.

KEYWORDS

순차패턴(Sequential patterns), 발생 간격 제한 조건(Gap-constraint), 순차 데이터 스트림(Sequence data streams), 순차패턴 마이닝(Sequential pattern mining)

Citation status

* References for papers published after 2023 are currently being built.

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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65