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數量化與模糊化序列效益探勘之研究 = A Study on Quanti...
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國立高雄大學資訊工程學系碩士班
數量化與模糊化序列效益探勘之研究 = A Study on Quantitative and Fuzzy Sequential Utility Mining
紀錄類型:
書目-語言資料,印刷品 : 單行本
並列題名:
A Study on Quantitative and Fuzzy Sequential Utility Mining
作者:
黃新程,
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:
2013[民102]
面頁冊數:
107面圖,表格 : 30公分;
標題:
資料挖掘
標題:
Data mining
電子資源:
http://handle.ncl.edu.tw/11296/ndltd/83796149986328783913
附註:
參考書目:面91-96
附註:
102年10月31日公開
附註:
內容為英文
摘要註:
由於序列效益探勘的應用相當廣泛,因此在知識挖掘領域是一個新興且有趣的研究議題。序列效益探勘不只考慮序列中各個物品的數量、利潤,還考慮了一條序列中物品的出現順序以找出感興趣的序列樣式,並可幫助管理者找出潛在的市場營銷知識和做出適當的決策。本文的第一部分因此針對數量化序列效益樣式探勘進行探討,相對於傳統的序列效益樣式,本文多考慮了數量區間的因素,而要如何得到適當的數量區間以及保持向下封閉性等問題使得此問題比傳統的序列效益樣式探勘更加的困難。基於上述原因,本文提出了一個有效的上界模型來保持向下封閉性,以及一個合併不同數量的機制來決定一個物品適合的數量區間。接著,為了使量化序列樣式可以更簡單也更接近人類的思維,本文的第二部份提出模糊效益序列樣式探勘的方法其結合了模糊集合概念來找出包含口語意義的高效益序列樣式。此外,本文也定義了一個新的模糊效益公式來評估一個語意化樣式在序列中的效益值,及提出一個模糊上界模型來減少在量化資料庫中搜尋高模糊效益序列樣式過程的空間。實驗的結果顯示,本文所提出的兩種序列樣式探勘方法在不同的參數設定下,對於探勘結果之有效性及執行效能皆有不錯的表現。 Sequential utility pattern mining is an interesting and emerging issue in knowledge discovery with wide applications. It considers not only the quantities and profits of items but also the occurrence order of items in sequences to get useful patterns, which may then help managers find out potential marketing knowledge and make appropriate decisions. In the first part of the thesis, we handle quantitative sequential utility pattern mining with the consideration of quantitative values of items. The problem is more difficult than traditional sequential utility pattern mining since it has to discover proper quantitative intervals of items and doesn’t satisfy the downward-closure property. Hence, an effective upper-bound model is developed to keep the property, and a merging method is designed to decide quantitative intervals of items in sequences. Moreover, to make the patterns simple and comprehensible to human beings, in the second part of the thesis, the fuzzy set concept is adopted to find interesting high utility se-quential patterns with linguistic meaning. We thus introduce another new research issue named fuzzy utility sequential pattern mining. In particular, a new fuzzy utility function is developed to evaluate the linguistic benefit of a pattern in a sequence, and an effective fuzzy upper-bound model is developed to reduce the search space of finding high fuzzy utility sequential patterns from a quantitative sequence database. The experimental results show the effectiveness of the two types of patterns and the performance of the proposed mining approaches under different parameter settings.
數量化與模糊化序列效益探勘之研究 = A Study on Quantitative and Fuzzy Sequential Utility Mining
黃, 新程
數量化與模糊化序列效益探勘之研究
= A Study on Quantitative and Fuzzy Sequential Utility Mining / 黃新程撰 - [高雄市] : 撰者, 2013[民102]. - 107面 ; 圖,表格 ; 30公分.
參考書目:面91-96102年10月31日公開內容為英文.
資料挖掘Data mining
數量化與模糊化序列效益探勘之研究 = A Study on Quantitative and Fuzzy Sequential Utility Mining
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由於序列效益探勘的應用相當廣泛,因此在知識挖掘領域是一個新興且有趣的研究議題。序列效益探勘不只考慮序列中各個物品的數量、利潤,還考慮了一條序列中物品的出現順序以找出感興趣的序列樣式,並可幫助管理者找出潛在的市場營銷知識和做出適當的決策。本文的第一部分因此針對數量化序列效益樣式探勘進行探討,相對於傳統的序列效益樣式,本文多考慮了數量區間的因素,而要如何得到適當的數量區間以及保持向下封閉性等問題使得此問題比傳統的序列效益樣式探勘更加的困難。基於上述原因,本文提出了一個有效的上界模型來保持向下封閉性,以及一個合併不同數量的機制來決定一個物品適合的數量區間。接著,為了使量化序列樣式可以更簡單也更接近人類的思維,本文的第二部份提出模糊效益序列樣式探勘的方法其結合了模糊集合概念來找出包含口語意義的高效益序列樣式。此外,本文也定義了一個新的模糊效益公式來評估一個語意化樣式在序列中的效益值,及提出一個模糊上界模型來減少在量化資料庫中搜尋高模糊效益序列樣式過程的空間。實驗的結果顯示,本文所提出的兩種序列樣式探勘方法在不同的參數設定下,對於探勘結果之有效性及執行效能皆有不錯的表現。 Sequential utility pattern mining is an interesting and emerging issue in knowledge discovery with wide applications. It considers not only the quantities and profits of items but also the occurrence order of items in sequences to get useful patterns, which may then help managers find out potential marketing knowledge and make appropriate decisions. In the first part of the thesis, we handle quantitative sequential utility pattern mining with the consideration of quantitative values of items. The problem is more difficult than traditional sequential utility pattern mining since it has to discover proper quantitative intervals of items and doesn’t satisfy the downward-closure property. Hence, an effective upper-bound model is developed to keep the property, and a merging method is designed to decide quantitative intervals of items in sequences. Moreover, to make the patterns simple and comprehensible to human beings, in the second part of the thesis, the fuzzy set concept is adopted to find interesting high utility se-quential patterns with linguistic meaning. We thus introduce another new research issue named fuzzy utility sequential pattern mining. In particular, a new fuzzy utility function is developed to evaluate the linguistic benefit of a pattern in a sequence, and an effective fuzzy upper-bound model is developed to reduce the search space of finding high fuzzy utility sequential patterns from a quantitative sequence database. The experimental results show the effectiveness of the two types of patterns and the performance of the proposed mining approaches under different parameter settings.
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