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姓名 張斯凱(Zue-Kai Chung)  查詢紙本館藏   畢業系所 資訊管理學系
論文名稱 探討高頻率價格樣式的知識挖掘
(Knowledge Discovery of Mining Frequent Priced Pattern)
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摘要(中) 資料挖掘的技術能夠找出大量資料中隱含的資訊,其中透過關聯規則的挖掘,能夠應用在零售業與百貨業中的購物籃分析上,可幫助行銷人員更有效地規畫行銷策略,對於交叉銷售、客戶區隔、搭配購買與商品型錄的設計上都有相當大的幫助。在零售業與百貨業之中,價格一直是影響消費者購買行為的重要因素,但是過去很少有關聯規則的分析技術,將商品價格水準的變化納入關聯規則的研究中,從這個角度去觀察,會產生許多有趣的問題。傳統關聯規則只能找出經常被共同購買的商品,而在加入價格水準的因素後,更能夠幫助企業有效地了解在各種不同的價格期間內,商品組合的實際銷售表現,進一步輔助企業來評估各種較佳的商品組合訂價。
本研究提出一套完整的分析架構,改良關聯規則的挖掘方法,加入價格與數量的維度,此方法能夠考量不同價格期間的Support計算方式,得到每個樣式在不同價格組合之下應有的Support值。此分析架構能夠從大量的交易資料中,挖掘出具有價格水準的高頻率樣式,並能針對樣式在不同價格組合期間內的銷售表現,進行事實的觀察與透過分析後的建議。
最後以真實資料進行實驗,挖掘出隱含在當中的高頻率價格樣式,並依價格組合對樣式的銷售表現影響加以歸類,將價格樣式分為9個種類;另外也對原本的高頻率樣式進行了樣式價格變異的測試。最後從實驗結果中舉出幾個實例,顯示我們所提出的方法,確實能提供更多關於價格促銷的有用資訊,對於評估促銷活動的反應及整體促銷策略的制定上,都能給予很大的幫助。
摘要(英) Association rule mining is very useful for retail business, including of cross sell, customers segment, bundle buying, and so on. Price issue is an important factor in real business environment, but there are few studies which discussed the relation between association rules and price of products. This paper presents an integral framework which can find frequent patterns under price factor. The framework also can provide the sale fact in sale data and analysis the possible suggestion according to the fact. We use real supermarket data on experiment. The actual examples of experimental results show that the framework which we present is useful for marketing or promotion.
關鍵字(中) ★ 資料挖掘
★ 關聯規則
★ 購物籃分析
★ 價格
關鍵字(英) ★ Association Rules
★ Data Mining
★ Market Basket Analysis
★ Price
論文目次 第一章 緒論 1
第二章 相關文獻探討 4
第一節 訂價(Pricing) 4
第二節 購物籃分析 6
第三節 關聯規則 6
第四節 時間關聯規則 7
第三章 定義 9
第四章 價格樣式的挖掘 14
第一節 建立IP-Tree與挖掘1-Large Itemset 16
第二節 產生Ck及挖掘k-Large Itemset 20
第三節 每階段候選的產生 26
第四節 篩選門檻的制定 30
第五節 潛在分析 32
第五章 實例說明 49
第六章 實驗模擬 58
第一節 實驗設計 58
第二節 參數調整 63
第三節 實驗結果 64
第四節 實例分析 66
第七章 結論與未來研究方向 75
參考文獻 77
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指導教授 陳彥良(Yen-Liang Chen) 審核日期 2004-6-16
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