基於連續長度編碼之關聯法則挖掘法

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Title:	基於連續長度編碼之關聯法則挖掘法
Other Titles:	An association rules miner based on run length encoding
Authors:	謝宗豪 Hsieh, Tsung-hao
Contributors:	資訊管理學系碩士班邱宏彬 Hung-pin Chiu
Keywords:	資料探勘;資料壓縮;關聯規則 Association Rules;Data Compression;Data Mining
Date:	2008
Issue Date:	2015-05-10 15:50:32 (UTC+8)
Abstract:	說到關聯規則是這幾年來非常熱門所討論的話題，在各行各業中也都慢慢的重視關聯規則的重要性與實用性，然而在演算法的處理執行效率將是大家所關心的重點。在早期在關聯規則演算法是將會員資料庫相關交易記錄存在資料庫中，然後再進行資料探勘，因為資料處理都在硬碟中運作，所以在效率處理上，執行速度都不是很理想，相對的降低了資料探勘的效率與速度。　　　　我們所提出的方法即可以改變上述的面臨的問題，方法為「連續長度編碼方法(Run-length Encoding RLE)」，用編碼技巧方法進在主記憶體中壓縮資料，進行探勘，在其探勘過程無須解壓縮編碼，進而增加探勘之效率。　　It is very hot topics discussed over these several years to talk about the related rule, importance and practicability with related and regular attention slowly too in all trades and professions, but it will be a focal point that everybody cares about that the treatment performing the algorithm carries out efficiency.It stores member's database relevant trade record in the database to perform algorithms in the related rule in early days, then carry on materials prospect, because materials punish operation of the hard disk, so in efficiency is dealt with, it is not all very ideal to carry out the speed, efficiency and speed that the relative reducing materials prospect.　　　　Question the method can change above-mentioned facing put forward by us, the method is ' coding method of the continuous length (Run-length Encoding RLE) ',it is by code skill enter method because mainly whether among storing device compress by materials, it is prospect not to go on, needn't be decompressed and encoded to prospect course in it, and then increase the efficiency prospected!
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