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Semi-Skylines and Skyline Snippets
Skyline evaluation techniques (also known as Pareto preference queries) follow a common paradigm that eliminates data elements by finding other elements in the data set that dominate them. To date already a variety of sophisticated Skyline evaluation techniques are known, hence Skylines are considered a well researched area.
This book presents Semi-Skylines as a novel concept for several challenging Skyline evaluation and optimization techniques. Among other things Semi-Skylines can be used effectively for algebraic optimization of constrained Skyline queries. Moreover, the problem of Skyline queries with very large result sets is considered. Using the concept of Skyline Snippets a subset of the complete Skyline can be computed without any pre-computed index structure.
Markus Endres was born 1976. From 1998 to 2004 he studied Mathematics and Computer Science at the University of Augsburg. Afterwards he worked as a Software Engineer in an internationally active company. Since 2005 he works as a researcher for the Chair of Databases and Information Systems at the University of Augsburg. In 2011 he received his doctor's degree for the thesis presented in this book.