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- 저자 : Saradhi.T (검색결과 2 건)
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Applying Z-Curve Technique to Compute Skyline Set in Multi Criteria Decision Making System
T. Vijaya Saradhi,Kodukula Subrahmanyam,P. Venkateswara Rao,Hye-jin Kim 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.12
The skyline queries are the best tools to be used in distributed multi criteria decision making of web based applications for user commendations. However, as the Data dimensions are increasing size of dominance set and skyline set is also increasing. Increasing dimensionality becomes the major problem with real word databases. In skyline computation major cost depends on finding dominance tests between high dimensional objects and the order in which they are accessing. Space filling Z-curve is the best suitable way to address the challenges in skyline computation. In this proposed work, we incorporated Z-curve with optimized skyline boundary detection algorithm to effective access and early pruning. In this paper efficient hybrid index structure was proposed which takes the advantage of sorting and partition approaches to improve the storage and search efficiency. Experimental results show that our propose approach is better than the previous static skyline computation techniques in terms of searching and finding skyline set.
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Vijaya Saradhi.T,Kodukula Subrahmanyam,Debnath Bhattacharyya,Tai-hoon Kim 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.8
A skyline of a n-dimensional data contains the data objects that are not dominated by any other data object on all dimensions. However, as the number of data dimensions increases the probability of domination points become very low, accordingly the number of points in the skyline becomes large. Also skyline search space has been identified as the key problem in real-time multidimensional databases. None of the traditional search techniques include the use of dimensionality reduction to optimize the search space. Skyline query computation on the server consecutively reduces the amount of data transferred between the server sites. Traditional static lower bound and upper bound probability computation will increase the number of non-dominance points. In this proposed work, an optimized skyline boundary detection algorithm is used to filter the skyline objects and pruning the local probability. Also, global probability computation was improved on the large skyline databases in order to minimize the search space and storage .The experimental results show that the efficiency of the proposed approach compared to traditional static skyline bound techniques in terms of time and search space are concerned.
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