博碩士論文 90423023 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊管理學系zh_TW
DC.creator林佳生zh_TW
DC.creatorChia-Sheng Linen_US
dc.date.accessioned2003-7-5T07:39:07Z
dc.date.available2003-7-5T07:39:07Z
dc.date.issued2003
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=90423023
dc.contributor.department資訊管理學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract近年來序列規則越來越重要了,傳統挖掘序列規則的方法都是建構在相同的方式上,也就是利用單一門檻值來挖掘那些出現次數超過門檻值的序列規則。利用單一門檻值的方法意味著所有的項目有著相似的特性,或者說它們出現在資料庫中的頻率類似,真實世界中並不常發生這樣的情形。 我們在這篇論文中首先延伸傳統單一門檻值來挖掘那些滿足不同門檻值的序列規則,接著設計了一個叫做MS-PrefixSpan的演算法。MS-PrefixSpan最主要的想法是以條件最小支持度當作門檻值來過濾投影資料庫中的項目,如果項目在投影資料庫中出現的次數超過門檻值,則將項目視為候選且長度為一的序列規則。條件最小支持度會依據每個投影資料庫逐漸調整以反映出每個最大序列規則實際的最小支持度。此外為了強調MS-PrefixSpan恰好可以找到所有的最大序列規則,我們提供了一個定理來說明MS-PrefixSpan的正確性。最後,我們的實驗結果顯示MS-PrefixSpan的確可以大量地減少時間和產生出的序列規則。zh_TW
dc.description.abstractSequential mining is becoming more and more important recently. Traditional sequential pattern mining algorithms used the same model, i.e., finding all sequential patterns that satisfy one user-specified minimum support. However, using only one single minimum support implies that all items in the data are of the same nature and/or have similar frequencies in the database. This is not often the case in real-life applications. In this paper, first we extended traditional one minimum support for all sequential patterns with multiple item supports. Second, we developed an effective algorithm called MS-PrefixSpan. Its general idea is using a conditional minimum support as a threshold to qualify items in each projected database for candidate length-1 sequential patterns. According to each projected database the conditional minimum support is gradually adjusted to reflect the actual minimum support of each maximal sequential pattern. Besides, in order to claim that MS-PrefixSpan can find all and only all maximal sequential patterns satisfying their own MSSP, we also provide a theorem to prove the correctness of MS-PrefixSpan. Third, our experimental result shows that MS-PrefixSpan indeed can substantially reduce the execution time and the number of produced sequential patterns.en_US
DC.subject資料挖礦zh_TW
DC.subject序列規則zh_TW
DC.subject多重門檻值zh_TW
DC.subjectPrefixSpanen_US
DC.subjectMultiple Minimum Supportsen_US
DC.subjectData Miningen_US
DC.subjectSequential Patternsen_US
DC.title利用多重門檻值挖掘序列規則zh_TW
dc.language.isozh-TWzh-TW
DC.titleMining Sequential Patterns with Multiple Minimum Supportsen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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