新的相似樣型分群法及其在產業的應用

A novel approach for pattern-similarity clustering and its application in industry

黃効晟(Xiauo-chen Huang)

指導教授 ： 吳建文

國立臺北科技大學/管理學院/工業工程與管理研究所/碩士(2009年)

摘要

以樣型為基礎的分群方法(pattern-based clustering)在近幾年來都已廣泛地被研究，主要是針對樣型間的相似性來作為分群標準。其對於一些應用領域是相當重要的。例如：DNA微陣列(DNA microarray)、電子商務(E-commerce)的應用…等等。
其中一種pattern-based clustering模型稱為pCluster，而本篇論文將提出一個新的pCluster求解演算法，是利用資料探勘(Data Mining)領域中尋找高頻項目集(frequent itemset)的概念來融入此演算法中，使我們能順利找出pCluster。

關鍵字

子空間分群 ； 樣型相似性

並列摘要

Pattern-based clustering has been studied intensively in recent years. This kind of clustering model focuses on the similarity between patterns. Such clusters are important for some applications, e.g. DNA microarray and E-commerce.
An example of pattern-based clustering models is called pCluster. In this study we propose a new approach to find the pCluster. Our approach utilizes the Apriori algorithm, which is a well known algorithm in the data mining field. We can find every pCluster by using our approach.

並列關鍵字

subspace clustering ； pattern similarity

參考文獻

[10] Jian Pei, Xiaoling Zhang, Moonjung Cho, Haixun Wang, and Philip S.Yu . ”On Mining Maximal Pattern-Based Clusters.” Data Mining and Knowledge Discovery, Springer

[14]R. Agrawal, J. Gehrke, D. Gunopulos, and P. Raghavan. ”Automatic subspace clustering of high dimensional data for data mining applications.” In Proceedings of the 1998 ACM SIGMOD international conference on Management of data, pages 94-105. ACM Press, 1998.

[2] C. C. Aggarwal, C. Procopiuc, J. Wolf, P. S. Yu, and J. S. Park. “Fast algorithms for projected clustering.“ In SIGMOD, 1999.

[3] C. C. Aggarwal and P. S. Yu. “Finding generalized projected clusters in high dimensional spaces.” In SIGMOD, pages 70–81, 2000.

[4] Daxin Jiang, JianPei, Aidong Zhang .”A General Approach to Mining Quality Pattern-Based Clusters from Microarray Data.” Lecture notes in computer science ISSN 0302-9743