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題 名 | 增進Apriori演算法探勘關聯規則=An Efficient Improved Apriori Algorithm for Mining Association Rules |
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作 者 | 陳垂呈; 陳宗義; | 書刊名 | 資訊科學應用期刊 |
卷 期 | 5:2 2009.12[民98.12] |
頁 次 | 頁71-85 |
分類號 | 312.13 |
關鍵詞 | 資料探勘; 關聯規則; Apriori; MQA-1; Data mining; Association rule; |
語 文 | 中文(Chinese) |
中文摘要 | 本論文以交易資料為探勘的資料來源,每一筆交易資料包含消費者曾經購買的產品項目,文中修改Apriori演算法對是否成為候選項目組的判斷方式,加入項目組之組合重複次數的概念,設計兩個演算法分別探勘關聯規則、及包含項目數量的關聯規則,稱之為improved_Apriori演算法及improved_MQA-1演算法。從實驗評估中顯示,improved_Apriori演算法及improved_MQA-1演算法可分別有效提升Apriori演算法、及MQA-1演算法的執行效能。 |
英文摘要 | This paper uses transaction data as the source data of mining. Each transaction data contains a consumer ever bought product items. We modify the approach of determining candidate itemsets of the Apriori algorithm, and add the idea of the number of joining repetition of itemsets. Two algorithms, called improved_Apriori and improved_MQA-1, are proposed to mine association rules and association rules including the quantities of items, respectively. The experiments show that the improved_Apriori algorithm and the improved_MQA-1 algorithm can effectively improve the performance of the Apriori algorithm and the MQA-1 algorithm, respectively. |
本系統中英文摘要資訊取自各篇刊載內容。