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Separator Database and SPM-Tree Framework for Mining Sequential Patterns Using PrefixSpan with Pseudoprojection

Dhany Saputra, Dhany (2008) Separator Database and SPM-Tree Framework for Mining Sequential Patterns Using PrefixSpan with Pseudoprojection. Masters thesis, Universiti Teknologi Petronas.

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Abstract

Sequential pattern mining is a new branch of data, mining science that solves inter transaction pattern mining problems. Efficiency and scalability on mining complete set of patterns is the challenge of sequential pattern mining. A comprehensive performance study has been reported that PrefixSpan, one of the sequential pattern mining algorithms,o utperformsG SP,S PADE, as well as FreeSpanin most casesa, nd PrefixSpan integratedw ith pseudoprojectionte chnique is the fastest among those tested algorithms. Nevertheless, Pseudoprojection technique, which requires maintaininga nd visiting the in-memorys equenced atabasefr equentlyu ntil all patterns are found, consumes a considerable amount of memory space and induces the algorithm to undertake many redundant and unnecessary checks to this copy of original databasebin to memory when the candidate patterns are examined.Moreover, improper management of intermediate databases may adversely affect the execution time and memory utilization. In the present work, Separator Database is proposed to improve PrefixSpan with pseudoprojection through early removal of uneconomical in-memory sequenced atabasew, hilst SPM-TreeF rameworki s proposedt o build the intermediated atabases.B y means of proceduresf or building index set of longer patterns using Separator Database, some procedure in accordance to in-memory sequenced atabasec an be removed,t hus most of the memory spacec an be released and some obliteration of redundant checks to in-memory sequence database reduce the executiont ime. By storing intermediated atabasesin to SPM-Tree Framework,t he sequenced atabasec an be storedi nto memory and the index set may be built. Using Java as a case study, a series of experiment was conducted to select a suitable API classn amedC ollections for this framework.The experimental results show that Separator Database always improves, exponentially in some cases, PrefixSpan with pseudoprojection. The results also show that in Java,A ArrayList is the most suitable choice for storing Object and ArrayIntList is the most suitable choice for storing integer data.

Item Type: Thesis (Masters)
Subject: T Technology > T Technology (General)
Divisions: ?? sch_ecs ??
Depositing User: Users 5 not found.
Date Deposited: 11 Jan 2012 12:18
Last Modified: 19 Jan 2017 15:49
URI: http://utpedia.utp.edu.my/id/eprint/1059

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