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題名:應用FP-Tree探勘多層次特徵規則
書刊名:管理資訊計算
作者:楊振銘謝韋芸
作者(外文):Yang, Cheng-mingHsieh, Wei-yun
出版日期:2015
卷期:4:特刊1
頁次:頁16-24
主題關鍵詞:資料探勘關聯規則多層次特徵規則Data miningAssociation rulesFP TreeMulti-level characteristic rule
原始連結:連回原系統網址new window
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  • 點閱點閱:13
利用資料探勘技術可以幫助企業探勘龐大資料庫中所隱含的資訊以增加競爭優勢,目前資料探勘中應用最廣的技術就是關聯規則,但大部分的演算法皆是在處理單一層次間的關聯規則,只單獨探討商品與商品間的相關性。在本篇研究中,提出了新的應用方式,簡稱為以FP-tree演算法探討多層次特徵規則,主要探討的是以消費者特徵與商品為組合,透過概念階層化架構,配合GID編碼及FP-Growth演算法,進而探勘出消費者特徵與商品間的高度關聯性。
Data mining techniques enable companies to explore meaningful patterns and rules from an enormous database. Association rule mining has been widely used. Many other relevant methods and researches have been published. However, most of the algorithms simply deal with the single level of association rules. In this paper, a new method "The FP-tree Algorithm for Mining the Multi-level Characteristic Rule" is proposed. The purpose of this study is to investigate the highly related association rules among customers’ characteristics and goods. It is expected that the FP-tree algorithm helps the users obtain meaningful association rules and put the data mining techniques into practice.
期刊論文
1.Fayyad, U. M.(1996)。Data Mining and Knowledge Discovery: Making Sense out of Data。IEEE Expert,11(5),20-25。  new window
2.Abou-Elela, S. I.、Haleem, H. A.、Abou-Taleb, E.、Ibrahim, H. S.(2007)。Application of Cleaner Production Technology in Chemical Industry: A Near Zero Emission。Journal of Cleaner Production,15(18),1852-1858。  new window
3.Agrawal, Rakesh、Imielinski, Tomasz、Swami, Arun(1993)。Database mining: A performance perspective。IEEE Transactions on Knowledge and Data Engineering,5(6),914-925。  new window
會議論文
1.Han, J.、Fu, Y.(1995)。Discovery of multiple-level association rules from large databases。The 21st International Conference on Very Large Data Bases,420-431。  new window
2.Wur, S. Y.、Leu, Yungho(1999)。An Effective Boolean Algorithm for Mining Association Rules in Large Databases。6th International Conference on Database Systems for Advanced Applications。IEEE。179-186。  new window
3.Agrawal, R.、Imielinski, T.、Swami, A.(1993)。Association Rule between Sets of Items in Large Databases。ACM SIGMOD International Conference on Management of Data,207-216。  new window
4.Agrawal, R.、Srikant, R.(1994)。Fast algorithms for mining association rules in large database。The 20th International Conference on Very Large Data Bases。Morgan Kaufmann Publishers Inc.。478-499。  new window
5.Han, J.、Pei, J.、Yin, Y.(2000)。Mining frequent patterns without candidate generation。The 2000 ACM SIGMOD International Conference on Management of Data。ACM。1-12。  new window
學位論文
1.許智豪(2000)。在動態資料庫中作線上挖掘關聯式法則(碩士論文)。國立中興大學。  延伸查詢new window
圖書
1.Han, Jiawei、Kamber, Micheline(2001)。Data Mining: Concepts and Techniques。Academic Press。  new window
2.吳旭志、賴淑貞、Berry, Michael J. A.、Linoff, Gordon S.(2001)。資料採礦理論與實務--顧客關係管理的技巧與科學。台北:數博網資訊股份有限公司。  延伸查詢new window
3.曾憲雄、蔡秀滿、蘇東興、曾秋蓉、王慶堯著(2005)。資料探勘Data Mining。台北:旗標出版股份有限公司。  延伸查詢new window
 
 
 
 
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