Computational geometry: an introduction
Computational geometry: an introduction
Computing dominances inEn (short communication)
Information Processing Letters
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
Introduction to Algorithms
A Microeconomic View of Data Mining
Data Mining and Knowledge Discovery
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
DADA: a data cube for dominant relationship analysis
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Escaping a Dominance Region at Minimum Cost
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
On domination game analysis for microeconomic data mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
Skyframe: a framework for skyline query processing in peer-to-peer systems
The VLDB Journal — The International Journal on Very Large Data Bases
Identifying the Most Endangered Objects from Spatial Datasets
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Ranking strategies and threats: a cost-based pareto optimization approach
Distributed and Parallel Databases
Call to order: a hierarchical browsing approach to eliciting users' preference
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Multi-Source skyline queries processing in multi-dimensional space
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Energy-efficient skyline query optimization in wireless sensor networks
Wireless Networks
Monochromatic and bichromatic mutual skyline queries
Expert Systems with Applications: An International Journal
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Recent research on skyline queries has attracted much interest in the database and data mining community. Given a database, an object belongs to the skyline if it cannot be dominated with respect to the given attributes by any other database object. Current methods have only considered so-called min/max attributes like price and quality which a user wants to minimize or maximize. However, objects can also have spatial attributes like x, y coordinates which can be used to represent relevant constraints on the query results. In this paper, we introduce novel skyline query types taking into account not only min/max attributes but also spatial attributes and the relationships between these different attribute types. Such queries support a micro-economic approach to decision making, considering not only the quality but also the cost of solutions. We investigate two alternative approaches for efficient query processing, a symmetrical one based on off-the-shelf index structures, and an asymmetrical one based on index structures with special purpose extensions. Our experimental evaluation using a real dataset and various synthetic datasets demonstrates that the new query types are indeed meaningful and the proposed algorithms are efficient and scalable.