Vertical Fragmentation for Database Using FPClose Algorithm
محتوى المقال
الملخص
Vertical fragmentation technique is used to enhance the performance of database system and reduce the number of access to irrelevant instances by splitting a table or relation into different fragments vertically. The partitioning design can be derived using FPClose algorithm, which is a data mining algorithm used to extract the frequent closed itemsets in a dataset. A new design approach is implemented to perform fragmentation. A benchmark with different minimum support levels is tested. The obtained results from FPClose algorithm are compared with the Apriori algorithm.
الكلمات المفتاحية
data mining، partitioning، vertical fragmentation
التنزيلات
المراجع
M. Golfarelli, D. Maio and S. Rizzi, “Vertical Fragmentation of Views in Relational Data Warehouses,” in Atti del Settimo Convegno Nazionale Sistemi Evoluti per Basi di Dati (7th SEBD),1999, pp. 19-33.
Z. Elhoussaine, D. Aboutajdine and E. Abderrahim, “Complete algorithm for fragmentation in data warehouse,” in Proc. 7th WSEAS Int. Conf. Artif. Intell. Knowl. Eng. Data Bases, Feb.2008, pp. 537-540.
F. Marir, Y. Najjar, M. Y. AlFaress and H. I. Abdalla, "An enhanced grouping algorithm for vertical partitioning problem in DDBs," 2007 22nd Int. Sympo. Comput. Inf. Sci., Ankara, 2007,pp. 1-6, doi: 10.1109/ISCIS.2007.4456833.
M. Thenmozhi and K. Vivekanandan, "A comparative analysis of fragmentation selection algorithms for data warehouse partitioning,"2014 Int. Conf. Adv. Eng. Technol. Res. (ICAETR - 2014),Unnao, 2014, pp. 1-5, doi: 10.1109/ICAETR.2014.7012866.
H. Mahboubi and J. Darmont, “Enhancing XML Data Warehouse Query Performance by Fragmentation,” in Proc. 2009 ACM Symp. Appl. Comput., Mar. 2009, pp. 1555–1562, doi:10.1145/1529282.1529630.
S. Yeruva, P. V. Kumar and P. Padmanabham, "Design of distributed warehouse-a vertical fragmentation approach," in 2015 1st Int. Conf. Next Gener. Comput. Technol. (NGCT), Dehradun,2015, pp. 616-621, doi: 10.1109/NGCT.2015.7375195.
S. Benkrid, L. Bellatreche and H. Drias, "A Combined Selection of Fragmentation and Allocation Schemes in Parallel Data Warehouses,"2008 19th Int. Workshop Database Expert Syst. Appl.,Turin, 2008, pp. 370-374, doi: 10.1109/DEXA.2008.63.
N. Gorla and P. W. Betty, “Vertical Fragmentation in Databases Using Data Mining Technique,” Int. J. Data Warehous. Min., vol.4, no. 3, pp. 35-53, July 2008, doi: 10.4018/jdwm.2008070103.
G. Grahne and J. Zhu, “High performance mining of maximal frequent itemsets,” in 6th Int. Workshop High Perform. Data Min., 2003, p. 34.
M. Bouakkaz, Y. Ouinten and B. Ziani, "Vertical fragmentation of data warehouses using the FP-Max algorithm," 2012 Int. Conf.Innov. Inf. Technol. (IIT), Abu Dhabi, 2012, pp. 273-276, doi:10.1109/INNOVATIONS.2012.6207746.
R. R. Kumar and A. B. Prasad, “K Means Clustering Algorithm for Partitioning Data Sets Evaluated From Horizontal Aggregations,”IOSR J. Comput. Eng. (IOSR-JCE), vol. 12, no. 5, pp.45-48, Jul.-Aug. 2013, doi: 10.9790/0661-1254548.
Chi-wai Fung, K. Karlapalem and Qing Li, "An evaluation of vertical class partitioning for query processing in object-oriented databases," in IEEE Trans. Knowl. Data Eng., vol. 14, no. 5, pp.1095-1118, Sept.-Oct. 2002, doi: 10.1109/TKDE.2002.1033777.
G. Grahne and J. Zhu, "Fast algorithms for frequent itemset mining using FP-trees," in IEEE Trans. Knowl. Data Eng., vol. 17,no. 10, pp. 1347-1362, Oct. 2005, doi: 10.1109/TKDE.2005.166.[14] M. Lichman, “{UCI} Machine Learning Repository,” 2013. [Online]. Available: http://archive.ics.uci.edu/ml
P. Fournier-Viger, “The SPMF Open-Source Data Mining Library Version 2,” in Jt. Eur. Conf. Mach. Learn. Knowl. Discov. Databases, in Machine Learning and Knowledge Discovery in Databases, in Lecture Noyes in Computer Science, vol. 9853, pp.32-35, Sept. 2016.
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