On Skyline Queries and How to Choose from Pareto Sets View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Christoph Lofi , Wolf-Tilo Balke

ABSTRACT

Skyline queries are well known for their intuitive query formalization and easy to understand semantics when selecting the most interesting database objects in a personalized fashion. They naturally fill the gap between set-based SQL queries and rank-aware database retrieval and thus have emerged in the last few years as a popular tool for personalized retrieval in the database research community. Unfortunately, the Skyline paradigm also exhibits some significant drawbacks. Most prevalent among those problems is the so called “curse of dimensionality” which often leads to unmanageable result set sizes. This flood of query results, usually containing a significant portion of the original database, in turn severely hampers the paradigm’s applicability in real-life systems. In this chapter, we will provide a survey of techniques to remedy this problem by choosing the most interesting objects from the multitude of skyline objects in order to obtain truly manageable and personalized query results. More... »

PAGES

15-36

Book

TITLE

Advanced Query Processing

ISBN

978-3-642-28322-2
978-3-642-28323-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-28323-9_2

DOI

http://dx.doi.org/10.1007/978-3-642-28323-9_2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022217950


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