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Volume & Issue no: Volume 3, Issue 7, July 2014


Computing Skyline Points for Decision Making Applications
Author Name:
K.Swathi, B.Renuka Devi
ABSTRACT A skyline is a subset of points in the data set that are not dominated by any other points. Skyline queries, which return skyline points, are useful in many decision making applications that involve high dimensional data sets. Given a d-dimensional data set, a point p dominates another point q if it is better than or equal to q in all dimensions and better than q in at least one dimension. To evaluate manually these points it is possible, if the data is small but if it is high dimensional data, it is vulnerable. As the number of dimensions increases, the chance of one point dominating another point is very low. As such, the number of skyline points become too numerous to offer any interesting insights. Here are the algorithms for finding k-dominant skyline and processing algorithms and providing best insights. These algorithms answer different queries on both synthetic and real data sets efficiently.
Cite this article:
K.Swathi, B.Renuka Devi , " Computing Skyline Points for Decision Making Applications" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 3, Issue 7, July 2014 , pp. 164-171 , ISSN 2319 - 4847.
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