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研究生:江美靜
研究生(外文):Mei-Ching Chiang
論文名稱:有時間區間的循序挖掘
指導教授:陳彥良陳彥良引用關係
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊管理研究所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:34
中文關鍵詞:資料挖掘循序樣式
外文關鍵詞:data miningsequential pattern
相關次數:
  • 被引用被引用:9
  • 點閱點閱:276
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
以往一般的循序挖掘研究中所探討的循序樣式,只能得知樣式中項目之間的前後順序關係,但無法讓我們知道項目之間的發生是間隔多久的時間,例如”有70%的機會,顧客於某商店購買印表機後,他會再來購買掃描器,之後則會再來購買燒錄器”的循序樣式,我們能從中得到印表機、掃描器、燒錄器的購買順序之資訊,但是我們無法得知購買印表機、掃描器、燒錄器之間的間隔時間為多久,因此本文提出包含時間區間的循序挖掘之研究,以探勘出擁有更多資訊的時間區間循序樣式,例如”有70%的機會,顧客於某商店購買印表機後,在經過6個月後,他會再來購買掃描器,之後,再經過3個月,則會再來購買燒錄器”的時間區間循序樣式。以零售業為例,業主可以利用所挖掘出的時間區間循序樣式,以瞭解顧客的習慣、喜好和需求,並且預測出顧客在未來某段時間內的期望,達到在適當的時機內,向適當的顧客,提供適當的產品和服務,滿足顧客的所需與所求之目的。故時間區間循序樣式可為企業帶來競爭優勢或替個人帶來利益。
本研究的目的是要挖掘出在序列資料庫中的時間區間循序樣式,一方面我們對此時間區間循序挖掘問題作出相關的定義,另一方面,我們發展出兩種演算法 ─ I-Apriori和I-PrefixSpan以進行挖掘。最後的實驗分析中,我們將演算法實作成系統,以驗證方法的可行性,並測試此兩演算法的效能與scale-up的特性。從實驗結果中得知,I-PrefixSpan的效能和scale-up的能力皆勝過I-Apriori,為一個較佳的時間區間循序挖掘的演算法。
1.緒論1
2.相關研究與相關應用3
2.1.相關研究3
2.2.相關應用5
3.問題定義與說明8
4.演算法11
4.1.I-APRIORI演算法11
4.1.1.產生候選的時間區間序列12
4.1.2.計算候選的時間區間序列17
4.2.I-PREFIXSPAN演算法20
5.效能25
5.1.模擬資料的產生25
5.2.效能26
5.3.SCALE-UP29
6.結論31
參考文獻32
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