Title
Compressing and Querying Skypattern Cubes.
Abstract
Skypatterns are important since they enable to take into account user preference through Pareto-dominance. Given a set of measures, a skypattern query finds the patterns that are not dominated by others. In practice, different users may be interested in different measures, and issue queries on any subset of measures (a.k.a subspace). This issue was recently addressed by introducing the concept of skypattern cubes. However, such a structure presents high redundancy and is not well adapted for updating operations like adding or removing measures, due to the high costs of subspace computations in retrieving skypatterns. In this paper, we propose a new structure called Compressed Skypattern Cube (abbreviated CSKYC), which concisely represents a skypattern cube, and gives an efficient algorithm to compute it. We thoroughly explore its properties and provide an efficient query processing algorithm. Experimental results show that our proposal allows to construct and to query a CSKYC very efficiently.
Year
DOI
Venue
2019
10.1007/978-3-030-22999-3_36
ADVANCES AND TRENDS IN ARTIFICIAL INTELLIGENCE: FROM THEORY TO PRACTICE
Keywords
Field
DocType
Skypatterns,Pareto-dominance relation,Skypattern cubes
Subspace topology,Computer science,Theoretical computer science,Redundancy (engineering),Cube,Computation
Conference
Volume
ISSN
Citations 
11606
0302-9743
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Willy Ugarte184.91
Samir Loudni215221.48
Patrice Boizumault329431.56
Bruno Crémilleux437334.98
Alexandre Termier530327.82