An Optimized Vertical Fragmentation Approach
Hichame Chaalel1, Hafida Belbachir2
1Hichame Chaalel, Department of Computer Science, Laboratory Systems Signals Data, University of Science and Technology, Mohamed Boudiaf-Oran Algeria.
2Pr. Hafida Belbachir, Department of Computer Science, Laboratory Systems Signals Data, University of Science and Technology, Mohamed Boudiaf-Oran Algeria.
Manuscript received on 10 September 2013 | Revised Manuscript received on 19 September 2013 | Manuscript Published on 30 September 2013 | PP: 33-39 | Volume-3 Issue-4, September 2013 | Retrieval Number: D1172093413/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Vertical fragmentation in databases is considered as a difficult problem; it has attracted the interest of many researchers and has been the subject of several studies. In the literature, these studies suggest approaches to solving the problem of vertical fragmentation, these approaches always provide a solution, but we find no indication about the relevance of solutions, nor any clue about their qualities. In this study we propose an algorithm that seems be best suited to the problem of vertical fragmentation and especially gives a best solution. To validate our approach we compared our solution to two existing algorithms based on two early studies (Genetic algorithm & Apriori algorithm).
Keywords: Genetic Algorithm, Data Mining, Physical Design, Vertical Fragmentation.
Scope of the Article: Data Mining