Skyline query on uncertain data based on improved probabilistic constraint space algorithm

PCS algorithm is a non-indexing method to prune non-skyline objects. Its pruning rate is more than 90% when data dimension is no more than 4, however when data dimension exceeds 4 the pruning rate falls significantly. This article improved PCS algorithm to improve the pruning rate of high-dimension...

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Bibliographic Details
Published in2014 IEEE 5th International Conference on Software Engineering and Service Science pp. 929 - 932
Main Authors Dong Liming, Liu Qing Bao, Dai Changhua
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2014
Subjects
Buildings
Educational institutions
Indexing
IPCS
Laboratories
PCS
Probabilistic logic
Probability
Skyline
uncertain data
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Summary:PCS algorithm is a non-indexing method to prune non-skyline objects. Its pruning rate is more than 90% when data dimension is no more than 4, however when data dimension exceeds 4 the pruning rate falls significantly. This article improved PCS algorithm to improve the pruning rate of high-dimension case. The main idea of PCS is to prune the non-skyline objects by establishing the minimum probabilistic constraint space. Experiments and analysis prove that IPCS improved an average 10% increase in the pruning rate.
ISBN:1479932787
9781479932788
ISSN:2327-0586
DOI:10.1109/ICSESS.2014.6933717