Improved Prefixspan Algorithm and Its Application in Sequential Pattern Mining

Zhang Wei; Liu Feng; Teng Shao-hua

doi:10.3969/j.issn.1007-7162.2013.04.008

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Improved Prefixspan Algorithm and Its Application in Sequential Pattern Mining

更新时间：2026-05-27

- Improved Prefixspan Algorithm and Its Application in Sequential Pattern Mining
- Vol. 30, Issue 4, Pages: 49-54(2013)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1007-7162.2013.04.008
  CLC：
- Online First：30 December 2013，
  
  Published：2013
- 稿件说明：
移动端阅览
张巍, 刘峰, 滕少华. 改进的PrefixSpan算法及其在序列模式挖掘中的应用[J]. 广东工业大学学报, 2013, 30(4): 49-54.

Zhang Wei, Liu Feng, Teng Shao-hua. Improved Prefixspan Algorithm and Its Application in Sequential Pattern Mining[J]. 2013, 30(4): 49-54.
张巍, 刘峰, 滕少华. 改进的PrefixSpan算法及其在序列模式挖掘中的应用[J]. 广东工业大学学报, 2013, 30(4): 49-54. DOI： 10.3969/j.issn.1007-7162.2013.04.008.

Zhang Wei, Liu Feng, Teng Shao-hua. Improved Prefixspan Algorithm and Its Application in Sequential Pattern Mining[J]. 2013, 30(4): 49-54. DOI： 10.3969/j.issn.1007-7162.2013.04.008.

摘要

由于序列模式挖掘需要花费大量计算时间，并需要占用大量存储空间.减少计算量、节省存储空间开销成为序列模式挖掘的关键.因PrefixSpan 算法不产生候选，而适当应用Bitmap数据结构可避免重复扫描数据库，基于此，本文提出了BM-PrefixSpan算法，用于序列模式挖掘，设计并构造了PFPBM(Prefix of First Position on BitMap)表用于记录序列中的每个项在位图中第1次出现的位置.实验结果表明，BM-PrefixSpan算法综合了PrefixSpan和SPAM算法的优点，能够更快、更好地挖掘出序列模式.

Abstract

Because sequential pattern mining needs a lot of computing time and storage space

how to reduce the amount of calculation and storage space becomes the key of the sequential pattern mining algorithm. Combining the PrefixSpan algorithm with Bitmap data structure

this text proposes an improved sequential pattern mining algorithm BM-PrefixSpan. The PFPBM (Prefix of First Position on BitMap) table was designed and implemented. When a new item appeared in a sequence

it was recorded in the PFPBM table. The experimental results show that the BM-prefixspan algorithm mines sequential patterns faster and better than others.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Prediction of Short-Term Load Based on Big Data Mining

Classification Method Based on Dimension Reduction

Some Challenges in Clustering Analysis

Research on Fault Diagnosis and Prevention Based on Extension

Energy Management Strategy of Hybrid Locomotive Based on Road Condition Parameters

Related Author

Li Yan-yan

Liu Fei-ya

Gao Hong-ming

Lin Jun-jie

Cao Xi

Chen Li

Zhang Wei

Huo Ying-xiang

Related Institution

No data

AI问答

⁰