政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/32618

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/32618

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政大典藏 > College of Informatics > Department of Computer Science > Theses > Item 140.119/32618

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32618

Title:	探勘空間相關樣式之研究 Mining Frequent Spatial Co-relation Patterns
Authors:	黃郁君 Huang,Yu-Chun
Contributors:	沈錳坤 Huang,Man-Kwan 黃郁君 Huang,Yu-Chun
Keywords:	資料探勘空間相關樣式 data mining spatial co-relation pattern
Date:	2003
Issue Date:	2009-09-17 13:52:11 (UTC+8)
Abstract:	在這個資訊快速擴張的時代，許多種類的資料庫被應用在各式各樣的領域中。空間資料探勘即是一個例子，它在空間資料庫中探勘出頻繁的樣式以及空間關係。空間資料探勘是在空間資料庫中挖掘出有趣的、以前不知道的、但實際上是有用的樣式或空間關係。在本篇論文中，我們探勘空間序列的問題。我們主要討論兩個主題：空間相關樣式，以及空間相似相關樣式。關於空間相關樣式，我們提出以Apriori為基礎以及深度優先為基礎的解法。在空間相關相似樣式部分，我們提出兩個演算法AP-mine以及AS-mine來解決我們的問題。在AP-mine中，我們提出一個名為AP-tree的資料結構來有效率的挖掘出空間相關相似樣式。最後我們以實驗來驗證我們的演算法。 With the growth of data, a variety of databases are applied in many applications. Spatial data mining is an example, and it discovers patterns or spatial relations from large spatial databases. Spatial data mining is the process of discovering interesting and previously unknown, but potential useful patterns or spatial relations from large spatial databases. In this thesis, we explore the problem of spatial sequential pattern mining. The two issues spatial co-relation patterns and approximate spatial co-relation patterns will be discussed. We utilize Apriori-based method and depth-first based method to solve the problem of spatial co-relation patterns. About approximate co-relation spatial patterns, we propose two algorithms, named AP-mine and AS-mine. In AP-mine, we propose a data structure, named AP-tree, to efficient mining the approximate spatial co-relation patterns. Lastly, We also perform the experiments to evaluate our spatial co-relation pattern mining algorithms.
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Proceedings of SIAM International Conference on Data Mining, 2003.
Description:	碩士國立政治大學資訊科學學系 89753011 92
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0089753011
Data Type:	thesis
Appears in Collections:	[Department of Computer Science ] Theses

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