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最近有效知識之挖掘 = Mining of Up-to-date Eff...

吳怡穎

最近有效知識之挖掘 = Mining of Up-to-date Effective Knowledge

紀錄類型:	書目-語言資料,印刷品 : 單行本
並列題名:	Mining of Up-to-date Effective Knowledge
作者:	吳怡穎,
其他團體作者:	國立高雄大學
出版地:	[高雄市]
出版者:	撰者;
出版年:	2008[民97]
面頁冊數:	56面圖，表 : 30公分;
標題:	資料探勘
標題:	data mining
電子資源:	http://handle.ncl.edu.tw/11296/ndltd/68039985966061895261
附註:	指導教授：洪宗貝
附註:	參考書目：面45-47
摘要註:	關聯法則中最重要的一環在於萃取出感興趣及具有意義的頻繁項目。此外，時間性的資料探勘主要是考量在資料庫中分析具時間性的資料並發現出具時間性的樣式與規律。資料庫的內容會隨著時間的增加而與日俱增，然而管理者面對龐大的資料庫最感興趣的往往是最新的資訊。基於以上的論點，在本論文中我們提出一個最近有效之樣式的新概念，其融合了頻繁樣式探勘及時間性探勘的概念。一個最近有效之樣式由一個項目及與其最近有效的存活時間所組成，並且具有在原始完整的資料庫中可能不是頻繁項目，但在最近的一段時間內為有效的頻繁項目之特性。本論文中提出了兩個方法，第一個方法是提出一套能挖掘出最近有效之頻繁樣式的演算法，首先先把時序性的資料庫內容轉換成位元表以加快之後的執行時間，接著針對各個項目分別萃取出從目前的時刻往前找出最長的有效時間。在第二個方法中，我們擴展第一個演算法使得能針對隨著資料庫記錄不斷成長漸進式地維護已萃取出的最近有效之頻繁樣式。最後，我們利用一些實驗來驗證我們所提方法的有效性。實驗結果顯示利用最近有效之頻繁樣式的方法，可擷取出較傳統資料探勘方法更多之有效的頻繁樣式，特別是當自小支持度門檻較高時。 The most important part of data mining is that find out interesting and meaningful frequent patterns from database. Furthermore, temporal data mining is concerned with the analysis of temporal data and the discovery of temporal patterns and regularities. In this thesis, therefore, a new concept of up-to-date patterns is proposed, which is a hybrid of the frequent patterns mining and temporal mining. An up-to-date pattern is thus composed of an itemset and its correspond up-to-date lifetime, in which the user-defined minimum support threshold must be satisfied. An itemset may not be frequent (large) for an entire database but may be large up-to-date since the items seldom occurring early may often occur lately. Two approaches are proposed in this thesis. In the first approach, the proposed approach can mine more useful large itemsets than the conventional ones which discover large itemsets valid only for the entire database. It first translates the log database into an item-oriented bit-map representation to speed up the execution in the later mining process and then extracts large itemsets valid with the longest lifetime from the past to the current time. The second approach then extends the previous one, which maintains up-to-date patterns when new transactions are added. Furthermore, we define a new variable to record the extra lifetime of an itemset in the log database for incremental mining approach.At lest, experimental results show that the proposed algorithm is more effective than the traditional ones in discovering such up-to-date patterns especially when the minimum support threshold is high.

最近有效知識之挖掘 = Mining of Up-to-date Effective Knowledge
吳, 怡穎

最近有效知識之挖掘 = Mining of Up-to-date Effective Knowledge / 吳怡穎撰 - [高雄市] : 撰者, 2008[民97]. - 56面 ; 圖，表 ; 30公分.
指導教授：洪宗貝參考書目：面45-47.
資料探勘data mining

最近有效知識之挖掘 = Mining of Up-to-date Effective Knowledge
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