TY - GEN
T1 - Compressing and querying skypattern cubes
AU - Ugarte, Willy
AU - Loudni, Samir
AU - Boizumault, Patrice
AU - Crémilleux, Bruno
AU - Termier, Alexandre
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Pareto-dominance relation
KW - Skypattern cubes
KW - Skypatterns
UR - https://www.scopus.com/pages/publications/85068605603
U2 - 10.1007/978-3-030-22999-3_36
DO - 10.1007/978-3-030-22999-3_36
M3 - Contribución a la conferencia
AN - SCOPUS:85068605603
SN - 9783030229986
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 406
EP - 421
BT - Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings
A2 - Wotawa, Franz
A2 - Pill, Ingo
A2 - Koitz-Hristov, Roxane
A2 - Friedrich, Gerhard
A2 - Ali, Moonis
PB - Springer Verlag
T2 - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019
Y2 - 9 July 2019 through 11 July 2019
ER -