TY - GEN
T1 - Skyline view
T2 - 11th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2009
AU - Kim, Jinhan
AU - Lee, Jongwuk
AU - Hwang, Seung Won
PY - 2009
Y1 - 2009
N2 - Skyline queries have gained much attention as alternative query semantics with pros (e.g.low query formulation overhead) and cons (e.g.large control over result size). To overcome the cons, subspace skyline queries have been recently studied, where users iteratively specify relevant feature subspaces on search space. However, existing works mainly focuss on centralized databases. This paper aims to extend subspace skyline computation to distributed environments such as the Web, where the most important issue is to minimize the cost of accessing vertically distributed objects. Toward this goal, we exploit prior skylines that have overlapped subspaces to the given subspace. In particular, we develop algorithms for three scenarios- when the subspace of prior skylines is superspace, subspace, or the rest. Our experimental results validate that our proposed algorithm shows significantly better performance than the state-of-the-art algorithms.
AB - Skyline queries have gained much attention as alternative query semantics with pros (e.g.low query formulation overhead) and cons (e.g.large control over result size). To overcome the cons, subspace skyline queries have been recently studied, where users iteratively specify relevant feature subspaces on search space. However, existing works mainly focuss on centralized databases. This paper aims to extend subspace skyline computation to distributed environments such as the Web, where the most important issue is to minimize the cost of accessing vertically distributed objects. Toward this goal, we exploit prior skylines that have overlapped subspaces to the given subspace. In particular, we develop algorithms for three scenarios- when the subspace of prior skylines is superspace, subspace, or the rest. Our experimental results validate that our proposed algorithm shows significantly better performance than the state-of-the-art algorithms.
UR - http://www.scopus.com/inward/record.url?scp=70349336153&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349336153&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-03730-6_25
DO - 10.1007/978-3-642-03730-6_25
M3 - Conference contribution
AN - SCOPUS:70349336153
SN - 3642037291
SN - 9783642037290
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 312
EP - 324
BT - Data Warehousing and Knowledge Discovery - 11th International Conference, DaWaK 2009, Proceedings
Y2 - 31 August 2009 through 2 September 2009
ER -