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題名：線上關聯規則採掘之資料方體挑選
書刊名：電子商務學報
作者：林文揚／張耀升
作者(外文)：Lin, Wen-yang／Chang, Yao-sheng
出版日期：2008
卷期：10:4
頁次：頁849-883
主題關鍵詞：資料倉儲；資料採掘；線上分析處理；資料方體；啟發式演算法；Data warehousing；Data mining；OLAP；Data cube；Heuristic method
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近幾年來，利用資料倉儲所儲存的資料方體進行關聯規則採掘的概念逐漸受到重視，陸續有學者提出結合資料方體的採掘方法，並證實此種做法可大幅降低採掘的時間。然而這些研究都假設資料倉儲系統可儲存所有可能的資料方體，未探討當儲存空間有限時，如何選取適當的資料方體加以實體化，以縮短關聯規則採掘的時間。另一方面，過去有關資料方體實體化的選取問題的研究都是針對一般的SQL查詢或OLAP分析，未見有針對資料採掘查詢的研究。本研究的主要目的即在探討在有限的儲存空間下，如何根據使用者所下達的多維度關聯規則查詢，挑選適當的資料方體加以儲存，以減少回答查詢所需的時間。針對此問題，我們明確定義利用資料方體來進行線上關聯規則採掘的模式及其查詢成本的估算方式，並實作及比較幾種散發式挑選方法，在有限的儲存空間下挑選出最佳的資料方體的組合。
Recently, the concept of utilizing data cubes stored in a data warehouse to facilitate as¬sociation rule mining has attracted lots of attention. Researchers have proposed data cube based mining methods and proven that such cube-based approaches can significantly reduce the mining time. However, these studies all assume that the data warehouse can store all possible data cubes, disregarding the issue of how to select an appropriate subset of mater¬ialized data cubes with respect to a limited storage in order to minimize the total execution time of association queries. On the other hand, most researches for data cube selection prob¬lem focused mainly on SQL or OLAP queries; there is no work addressing the data cube selection issue for association queries. The main purpose of this study is to investigate under a limited storage and a given set of users' association queries how we can select appropriate set of data cubes to materialize to reduce the query execution time. To this end, we define a cost model for data cube selection problem for on1ine association mining and elaborate the cost estimation for association query. We implement and compare various heuristic algorithms to select suitable data cubes subject to the space constraint.
期刊論文
1.Yao, Xin、Choi, Chi-hon、Yu, Jeffrey Xu、Gou, Gang(2003)。Materialized View Selection as Constrained Evolutionary Optimization。IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews，33(4)，458-467。  new window
2.Tjioe, H. C.、Taniar, D.(2005)。Mining Association Rules in Data Warehouses。International Journal of Data Warehousing and Mining，1(3)，28-62。  new window
3.林文揚、張耀升(2005)。啟發式資料方體挑選方法之分析比較。資訊管理學報，12(2)，201-220。new window  延伸查詢new window
4.Hung, M. C.、黃美玲、Yang, D. L.、Hsueh, N. L.(2007)。Efficient Approaches for Materialized Views Selection in a Data Warehouse。Information Sciences，177(6)，1333-1348。  new window
5.Chaudhuri, S.、Dayal, U.(1997)。An Overview of Data Warehouse and OLAP Technology。ACM SIGMOD Record，26(1)，65-74。  new window
6.Han, J.(1998)。Toward On-line Analytical Mining in Large Databases。ACM SIGMOD Record，27(1)，97-107。  new window
7.Zhang, C.、Yao, X.、Yang, J.(2001)。An Evolutionary Approach to Materialized Views Selection in a Data Warehouse Environment。IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews，31(3)，282-294。  new window
8.Park, C. S.、Kim, M. H.、Lee, Y. J.(2002)。Finding an Efficient Rewriting of OLAP Queries Using Materialized Views in Data Warehouses。Decision Support Systems，32(4)，379-399。  new window
9.Han, J.、Lakshmanan, L. V. S.、Ng, R. T.(1999)。Constraint-based, Multi-dimensional Data Mining。IEEE Computer，32(8)，46-50。  new window
10.Kalnis, P.、Mamoulis, N.、Papadias, D.(2002)。View Selection Using Randomized Search。Data and Knowledge Engineering，42(1)，89-111。  new window
11.Lin, W. Y.、Kuo, I. C.(2004)。A Genetic Selection Algorithm for OLAP Data Cube。Knowledge and Information Systems，6(1)，83-102。  new window
會議論文
1.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
2.Shim, J.、Scheuermann, P.、Vingralek, R.(1999)。Dynamic Caching of Query Results for Decision Support Systems。0。254-263。  new window
3.Smith, J. R.、Castelli, V.、Jhingran, A.、Li, C. S.(1998)。Dynamic Assembly of Views in Data Cubes。0。274-283。  new window
4.Harinarayan, V.、Rajaraman, A.、Ullman, J. D.(1996)。Implementing Data Cubes Efficiently。0。205-2169。  new window
5.Ezeife, C. I.(1997)。A Uniform Approach for Selecting Views and Indexes in a Data Warehouse。0。151-160。  new window
6.Beyer, K. S.、Ramakrishnan, R.(1999)。Bottom-up Computation of Sparse and Iceberg Cubes。0。359-370。  new window
7.Deshpande, P. M.、Ramasamy, K.、Shukla, A.、Naughton, J. F.(1999)。Caching Multi-dimensional Queries Using Chunks。0。371-382。  new window
8.Hidber, C.(1999)。Online Association Rule Mining。The 1999 ACM SIGMOD International Conference on Management of Data，145-156。  new window
9.Yang, J.、Karlapalem, K.、Li, Q.(1997)。Algorithm for Materialized View Design in Data Warehousing Environment。0。136-145。  new window
10.Theodoratos, D.、Sellis, T.(1997)。Data Warehouse Configuration。0。126-135。  new window
11.Baralis, E.、Paraboschi, S.、Teniente, E.(1997)。Materialized View Selection in a Multidimensional Database。0。156-165。  new window
12.Fang, M.、Shivakumar, N.、Garcia-Molina, H.、Motwani, R.、Ullman, J. D.(1998)。Computing Iceberg Queries Efficiently。0。299-310。  new window
13.Shukla, A.、Deshande, P. M.、Naughtion, J. F.(1998)。Materialized View Selection for Multi-dimensional Datasets。0。156-165。  new window
14.Agrawal, S.、Chaudhuri, S.、Narasayya, V. R.(2000)。Automated Selection of Materialized Views and Indexes in SQL Databases。0。496-505。  new window
15.Lin, W. Y.、Su, J. H.、Tseng, M. C.(2002)。OMARS: The Framework of an Online Multidimensional Association Rules Mining System。0。  new window
16.Theodoratos, D.、Bouzeghoub, M.(2000)。A General Framework for the View Selection Problem for Data Warehouse Design and Evolution。0。1-8。  new window
17.Kamber, M.、Han, J.、Chiang, J. Y.(1997)。Metarule-guided Mining of Multidimensional Association Rules Using Data Cubes。0。207-210。  new window
18.Han, J.、Chee, S.、Chiang, J.(1998)。Issues for On-line Analytical Mining of Data Warehouses。0。21-25。  new window
19.Gunzel, H.、Albrecht, J.、Lehner, W.(1999)。Data Mining in a Multidimensional Environment。0。191-204。  new window
20.Alhajj, R.、Kaya, M.(2003)。Integrating Fuzziness into OLAP for Multidimensional Fuzzy Association Rules Mining。0。469-472。  new window
21.Gupta, H.(1997)。Selection of Views to Materialize in a Data Warehouse。0。98-112。  new window
22.Han, J.(1997)。OLAP Mining: An Integration of OLAP with Data Mining。0。1-11。  new window
23.Gupta, H.、Mumick, I. S.(1999)。Selection of Views to Materialize under a Maintenance Cost Constraint。0。453-470。  new window
24.Messaoud, R. B.、Rabaseda, S. L.、Boussaid, O.、Missaoui, R.(2006)。Enhanced Mining of Association Rules from Data Cubes。0。11-18。  new window
25.陳耀輝、劉宇昌、劉佳灝(1997)。在資料倉儲中選擇實體化視域之研究。0。72-77。  延伸查詢new window
26.林文揚、郭義中(2000)。應用於線上分析之資料方體的雙向貪婪挑選法。0。  延伸查詢new window
學位論文
1.Zhu, H.(1998)。On-line Analytical Mining of Association Rules，0。  new window
圖書
1.Han, Jiawei、Kamber, Micheline(2000)。Data mining: Concepts and techniques。Morgan Kaufmann Publishers。  new window
2.Jarke, M.(1984)。Common Subexpression Isolation in Multiple Query Optimization。Query Processing in Database Systems。0。  new window
 
 
 
 
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