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研究生:沈仁傑
研究生(外文):Ren_Jieh Shen
論文名稱:多商店下的關聯規則挖掘
指導教授:陳彥良陳彥良引用關係
指導教授(外文):Yen-Liang Chen
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:59
中文關鍵詞:資料挖掘關聯規則連鎖商店
外文關鍵詞:association ruledata mining
相關次數:
  • 被引用被引用:3
  • 點閱點閱:213
  • 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:0

從交易資料庫中利用關聯規則的挖掘可以找出商品之間的關聯性,對於行銷推廣、商品搭配、商品貨架設計、生產排程等有絕大的幫助。傳統關聯規則挖掘方式只能針對單店的環境來挖掘出關聯規則,但在連鎖系列商店中,各家商店為了提高競爭力,每一家商店在不同的地點及時節會販賣不一樣的商品。例如醫院附近連鎖店所販賣的醫療性用品、觀光地區附近所販賣的觀光性商品、夏天所販賣的冰品、以及冬天所販賣的火鍋、特殊節日所販賣的禮品等。傳統關聯規則挖掘方式對於這些季節性及地區性商品在計算support值時都一視同仁地處理。此種方式將會造成其support值的低估而忽略了該商品於短期內或某區域內造成熱賣的事實。
為了解決傳統關聯規則挖掘方式應用在多商店環境時所產生的問題,我們提出了包含時間地點的關聯規則挖掘方式,此方法在計算不同商品的support值時,必須考量到不同的商品具有不同的上架地點及時間,而不是一視同仁地處理,如此算出來的support值才是正確的。而對於正確的confidence值的計算方式,我們也另外提出一個演算法來解決。
最後實驗模擬的結果證明,傳統關聯規則挖掘方式如果應用在多商店的環境之下時,將會造成釵h地區性或季節性商品的關聯規則無法被挖掘出來,而使用包含時間地點的關聯規則挖掘方式時,將可以解決這些問題。


第一章緒論1
第二章定義6
第三章時間地點關聯規則的挖掘9
第一節建立PT_INTERVAL11
第二節1-ITEMSET 14
第三節N-ITEMSET 17
第四節CANDIDATE ITEMSET的產生18
第五節CONFIDENCE值的計算及規則的產生20
第四章實例說明25
第五章實驗模擬37
第一節實驗設計37
第二節參數設定40
第三節評量方式41
第四節實驗結果43
第五節被低估的SUPPORT值及CONFIDENCE值50
第六節相關應用51
第六章結論與未來展望53
參考文獻54
附錄58


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