Continuous Probabilistic Subspace Skyline Query Processing Using Grid Projections

Zhao, Lei, Yang, Yan-Yan and Zhou, Xiaofang (2014) Continuous Probabilistic Subspace Skyline Query Processing Using Grid Projections. Journal of Computer Science and Technology, 29 2: 332-344. doi:10.1007/s11390-014-1434-9

Author Zhao, Lei
Yang, Yan-Yan
Zhou, Xiaofang
Title Continuous Probabilistic Subspace Skyline Query Processing Using Grid Projections
Journal name Journal of Computer Science and Technology   Check publisher's open access policy
ISSN 1000-9000
Publication date 2014-03-01
Year available 2014
Sub-type Article (original research)
DOI 10.1007/s11390-014-1434-9
Volume 29
Issue 2
Start page 332
End page 344
Total pages 13
Place of publication New York, NY United States
Publisher Springer New York LLC
Language eng
Formatted abstract
As an important type of multidimensional preference query, the skyline query can find a superset of optimal results when there is no given linear function to combine values for all attributes of interest. Its processing has been extensively investigated in the past. While most skyline query processing algorithms are designed based on the assumption that query processing is done for all attributes in a static dataset with deterministic attribute values, some advanced work has been done recently to remove part of such a strong assumption in order to process skyline queries for real-life applications, namely, to deal with data with multi-valued attributes (known as data uncertainty), to support skyline queries in a subspace which is a subset of attributes selected by the user, and to support continuous queries on streaming data. Naturally, there are many application scenarios where these three complex issues must be considered together. In this paper, we tackle the problem of probabilistic subspace skyline query processing over sliding windows on uncertain data streams. That is, to retrieve all objects from the most recent window of streaming data in a user-selected subspace with a skyline probability no smaller than a given threshold. Based on the subtle relationship between the full space and an arbitrary subspace, a novel approach using a regular grid indexing structure is developed for this problem. An extensive empirical study under various settings is conducted to show the effectiveness and efficiency of our PSS algorithm.
Keyword Probabilistic query
Continuous query
Sliding Windows
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 4 times in Scopus Article | Citations
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