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1860799936539394048
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INTELEK Repository
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Online Access
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https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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2014-08-12 14:51:38
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Restricted Document
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7988
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UniSZA
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[1] M. K. Yusof and A. Azlan, “Comparative Study of Techniques in Reducing Inconsistent Data”, International Journal of Database Theory and Application, vol. 5, no. 1, (2012) March. [2] X. Wang, L. P. Huang, X. H. Yu and J. Q. Chen, “A Solution for Data Inconsistency in Data Integration”, Journal of Information Science and Engineering, vol. 27, (2011), pp. 681-695. [3] Z. Pawlak, “Rough Set and Data Analysis”, Proceedings of the Asian, (1996) December 11-14, pp. 1-6. [4] Z. Pawlak, “Rough Set” International Journal of Computer and Information Science, vol. 11, no. 5, (1982), pp. 341 – 356. [5] H. Sug, “An Efficient Method of Data Inconsistency Check for Very Large Relations”, International Journal of Computer Science and Network, vol. 7, no. 10, (2007). [6] H. Sug, “A Rough Set Based Data Inconsistency Checking Method for Relational Databases”, International Journal of Computer Science and Network, vol. 8, no. 11, (2008) November. [7] Z. Pawlak, “Rough Set”, International Journal of Computer and Information Science, vol. 11, no. 5, (1982), pp. 341 – 356. [8] L. Cavigue, A. B. Mendes and M. Funk, “Logic Analysis of Inconsistent Data (LAID)”, (2010). [9] H. Sug, “An Efficient Method of Data Inconsistency Check for Very Large Relations”, International Journal of Computer Science and Network, vol. 7, no. 10, (2007).
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3816-01-FH02-FIK-14-00966.pdf
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Google
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oai_dc
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https://intelek.unisza.edu.my/intelek/pages/view.php?ref=7988
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7988 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=7988 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Article Journal application/pdf 12 Adobe Acrobat Pro DC 20 Paper Capture Plug-in 1.7 Google 2014-08-12 14:51:38 3816-01-FH02-FIK-14-00966.pdf UniSZA Private Access Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database International Journal of Database Theory and Application Inconsistent data in database occurs due to increasing number of data. A suitable technique is needed to reduce inconsistent data from database. In this paper, fuzzy multi attribute decision making was chosen to reduce inconsistent data from database. This technique contains 5 steps which are deriving quality vector, scale the quality matrix, compute weighted Euclidean distance and select final alternative. An application was developed using java and oracle technology. Sample data was selected for experiments purposes. The result indicates fuzzy multi attribute decision making is a suitable technique in reducing inconsistent data from database. Algorithm in fuzzy multi attribute decision making is able to find out a correct object. 6 1 1-11 [1] M. K. Yusof and A. Azlan, “Comparative Study of Techniques in Reducing Inconsistent Data”, International Journal of Database Theory and Application, vol. 5, no. 1, (2012) March. [2] X. Wang, L. P. Huang, X. H. Yu and J. Q. Chen, “A Solution for Data Inconsistency in Data Integration”, Journal of Information Science and Engineering, vol. 27, (2011), pp. 681-695. [3] Z. Pawlak, “Rough Set and Data Analysis”, Proceedings of the Asian, (1996) December 11-14, pp. 1-6. [4] Z. Pawlak, “Rough Set” International Journal of Computer and Information Science, vol. 11, no. 5, (1982), pp. 341 – 356. [5] H. Sug, “An Efficient Method of Data Inconsistency Check for Very Large Relations”, International Journal of Computer Science and Network, vol. 7, no. 10, (2007). [6] H. Sug, “A Rough Set Based Data Inconsistency Checking Method for Relational Databases”, International Journal of Computer Science and Network, vol. 8, no. 11, (2008) November. [7] Z. Pawlak, “Rough Set”, International Journal of Computer and Information Science, vol. 11, no. 5, (1982), pp. 341 – 356. [8] L. Cavigue, A. B. Mendes and M. Funk, “Logic Analysis of Inconsistent Data (LAID)”, (2010). [9] H. Sug, “An Efficient Method of Data Inconsistency Check for Very Large Relations”, International Journal of Computer Science and Network, vol. 7, no. 10, (2007).
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| spellingShingle |
Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
|
| summary |
Inconsistent data in database occurs due to increasing number of data. A suitable technique is needed to reduce inconsistent data from database. In this paper, fuzzy multi attribute decision making was chosen to reduce inconsistent data from database. This technique contains 5 steps which are deriving quality vector, scale the quality matrix, compute weighted Euclidean distance and select final alternative. An application was developed using java and oracle technology. Sample data was selected for experiments purposes. The result indicates fuzzy multi attribute decision making is a suitable technique in reducing inconsistent data from database. Algorithm in fuzzy multi attribute decision making is able to find out a correct object.
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| title |
Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
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| title_full |
Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
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| title_fullStr |
Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
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| title_full_unstemmed |
Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
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| title_short |
Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
|
| title_sort |
reducing of inconsistent data using fuzzy multi attribute decision making for accessing data from database
|