基於約略集合的規則歸納新方法

A Novel Rough Set Based Approach of Rule Induction

許灝(Hao Hsu)

指導教授 ： 黃俊哲

國立暨南國際大學/管理學院/資訊管理學系/碩士(2018年)

摘要

隨著科技的進步，許多資料都改以電子化的方式記錄下來。在這些龐大的資料中往往隱含著一些有趣的趨勢、特徵或相關性等著我們去挖掘及分析。
近年來在大數據(Big Data)的興起，資料探勘(Data Mining)在知識管理(Knowledge Management)領域中已扮演了一個重要的技術，提供了一個可用來挖掘隱含在大量資料中具有價值與意義的知識。
在現有的資料探勘技術中，約略集合(Rough Set)是一個知識發現的工具，可以用來找出隱藏在龐大數據中的邏輯規律。然而，傳統的約略集合在產生最後決策規則的過程中會經由兩個階段才可產生，浪費了不必要的時間與空間，這在現今講求效率的時代中會有點出入，因此本研究提出一個新的歸納方法來減少因為找出決策規則所多消耗的時間以及記憶體的空間。

關鍵字

資料探勘 ； 約略集合理論 ； 層級分析法 ； 質數

並列摘要

With the advancement of technology, many materials have been recorded in an electronic way. In these large data often implies some interesting trends, characteristics or relevance waiting for us to dig and analysis.
In recent years, in the rise of Big Data, Data Mining has played an important role in the field of Knowledge Management, providing a valuable and meaningful knowledge that can be used to mine hidden data.
In Data Mining technology, Rough Set is a knowledge discovery tool that can be used to find the logic that is hidden in large data. However, the traditional set of abstracts can be generated through two stages in the process of generating the final decision rules, wasting unnecessary time and space, which will be a bit different in today's era of efficiency. Therefore, this study proposes a new inductive method to reduce the time spent on finding decision rules and the space of memory.

並列關鍵字

Data Mining ； Rough Set ； Analytic Hierarchy Process ； Prime Number

參考文獻

一、英文部分

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