Please use this identifier to cite or link to this item:
|Title:||SkyEngine: Efficient skyline search engine for continuous skyline computations|
|Citation:||Hsueh, Y.-L.,Zimmermann, R.,Ku, W.-S.,Jin, Y. (2011). SkyEngine: Efficient skyline search engine for continuous skyline computations. Proceedings - International Conference on Data Engineering : 1316-1319. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDE.2011.5767944|
|Abstract:||Skyline query processing has become an important feature in multi-dimensional, data-intensive applications. Such computations are especially challenging under dynamic conditions, when either snapshot queries need to be answered with short user response times or when continuous skyline queries need to be maintained efficiently over a set of objects that are frequently updated. To achieve high performance, we have recently designed the ESC algorithm, an Efficient update approach for Skyline Computations. ESC creates a pre-computed candidate skyline set behind the first skyline (a second line of defense, so to speak) that facilitates an incremental, two-stage skyline update strategy which results in a quicker query response time for the user. Our demonstration presents the two-threaded SkyEngine system that builds upon and extends the base-features of the ESC algorithm with innovative, user-oriented functionalities that are termed SkyAlert and AutoAdjust. These functions enable a data or service provider to be informed about and gain the opportunity of automatically promoting its data records to remain part of the skyline, if so desired. The SkyEngine demonstration includes both a server and a web browser based client. Finally, the SkyEngine system also provides visualizations that reveal its internal performance statistics. © 2011 IEEE.|
|Source Title:||Proceedings - International Conference on Data Engineering|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 10, 2018
checked on Nov 24, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.