Applying Fuzzy cluster index to improve searching in data warehouse
Keywords:Data Warehouse, Apriori Algorithm, Fuzzy Cluster Index (FCI), Fuzzy Rule.
AbstractData Warehouse (DW) is one of the solutions for decision-making process in a business organization. But it only stores data for managerial purpose and it has no intelligent mechanism for decision making. For improving the process of decision making and searching Data Warehouse (DW) of the medical resources (items), where this study includes an application on a Data Warehouse (DW) of medical resources (items).In this paper, we merged the fuzzy rule with cluster index technique. where The proposed technique is named Fuzzy Cluster Index technique (FCI) to improve and speed up Queries fuzzy rule and process of decision making and management medical (items), The performance evaluation of three data warehouse queries is focused in this paper by comparing with Fuzzy cluster index technique (FCI), Fuzzy Rule and Index-based Apriori Algorithm to observe the results of variable size dataset with respect to time. Eventually, the designed system was constructed and executed by using (C# version 2010) which is a visual and object oriented programming language. This proves the efficiency of the proposed system for improving searching in Data Warehouse (DW) and the decision support system for the medical items in a perfect way.
(1) Y. Bssil, “A Data Warehouse Design for A Typical University Information System”, LACSC – Lebanese Association for Computational Sciences Registered under No. 957, 2011, Beirut, Lebanon . Journal of Computer Science & Research (JCSCR) Vol. 1, No. 6, December 2012, pp. 12-17.
(2) R. Jindal1, and S. Taneja2 “COMPARATIVE STUDY OF DATA WAREHOUSE DESIGN APPROACHES: A SURVEY” 1 Associate Professor, Dept. of Computer Engineering, Delhi Technological University Formerly Delhi College of Engineering (DCE), Bawana Road, Delhi-42. 2 Research Scholar, Dept. of Computer Engineering, Delhi Technological University Formerly Delhi College of Engineering (DCE), Bawana Road, Delhi-42. International Journal of Database Management Systems ( IJDMS ) Vol.4, No.1, February 2012,pp.33-45.
(3) C. Gallo, and M. De Bonis, and M. Perilli “Data Warehouse Design and Management: Theory and Practice” IEEE MEMBERS. DIPARTIMENTO DI SCIENZE ECONOMICHE, MATEMATICHE E STATISTICHE UNIVERSIT`A DI FOGGIA Largo Papa Giovanni Paolo II, 1 - 71121 Foggia, Italy, Quaderno n. 07/2010,pp.1-18.
(4) D. Fasel, and K. Shahzad “A Data Warehouse Model for Integrating Fuzzy Concepts in Meta Table Structures” Information System Research Group Department of Informatics University of Fribourg Boulevard de Prolles 90 ,1700 Fribourg, Switzerland and Information Systems Laboratory Department of Computer and System Science Royal Institute of Technology (KTH) Forum 100, SE 164 40, Stockholm, Sweden,2010,pp.1-10.
(5) L. Sapir, and A. Shmilovici,”A Methodology for the Design of a Fuzzy Data Warehouse” Member IEEE, Lior Rokach,2009,pp.1-8.
(6) M. Kokate, and Sh. Karwa, and S. Suman, and Prof. R. Chavan, "Performance Enhancement Techniques of Data Warehouse" International Conference on Advanced Computing and Communication Technologies, 2011, pp.67-72.
(7) A. Kumar, and D. Singh, and Dr. V. Sharma, "Achieving Query Optimization Using Sparsity Management in OLAP System" International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT),2014,pp.797-801.
(8) Qader, B. A.,(2013), Applying the Concept of Knowledge Warehouse in Enterprise Resources Management, M.SC . Thesis, University of Anbar , Iraq .
(9) F. Kausar1, and Sh. Odah Al Beladi, and K. AL Shammari, "Comparative Analysis of Bitmap Indexing Techniques in Data Warehouse"International Journal of Emerging Technology and Advanced Engineering, VoL 4, no.1. 2014, pp.34-41.
(10) J. Zacek, and F. Hunka, " Data warehouse minimization with ELT fuzzy filter" Advances in Information Science and Applications, Vol II,2014,pp.450-454.
(11) Igodan C. E, and Akinyokun O.C, and O. Olatubosun, "ONLINE FUZZY-LOGIC KNOWLEDGE WAREHOUSING AND MINING MODEL FOR THE DIAGNOSIS AND THERAPY OF HIV/AIDS" International Journal of Computational Science and Information Technology, Vol.1, No.3, 2013,pp.27-40.
(12) M. El-Wessimy, and H. M.O. Mokhtar, and O. Hegazy, "ENHANCEMENT TECHNIQUES FOR DATA WAREHOUSE STAGING AREA" International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.3, No.6, 2013,pp.1-19.
(13) El. Aoulad Abdelouarit, and M. El Merouani, and A. Medouri, "The impact of indexes on data warehouse performance" International Journal of Computer Science Issues, Vol. 10, No 2, 2013, pp.34-37.
(14) K. Babar, and A. Gosain, "PREDICTING THE QUALITY OF OBJECT-ORIENTED
MULTIDIMENSIONAL (OOMD) MODEL OF DATA WAREHOUSE USING FUZZY LOGIC TECHNIQUE" (IJESAT), Vol 2, pp.1048-1054.
(15) Ms. R. Raval, and Prof. I. Rajput, and Prof. V. Gupta, " Survey on several improved Apriori algorithms" Journal of Computer Engineering (IOSR-JCE), Vol 9,2013,pp.57-61.
(16) A. Bansal, and S. Arora, "Performance Measurement of Indexing Techniques Used in Biomedical Databases" International Journal of Scientific & Engineering Research, Vol 3, 2012, pp.1-5.
(17) C. CIOLOCA, and M. GEORGESCU, "Increasing Database Performance using Indexes" Database Systems Journal, vol. II, no. 2, 2011, pp.13-22.