2024-03-29T05:03:43Z
https://tsukuba.repo.nii.ac.jp/oai
oai:tsukuba.repo.nii.ac.jp:00051833
2022-04-27T09:25:04Z
3048:1229
3048:1453
3:62:5591:1063
Scalable keyword search over relational data streams by aggressive candidate network consolidation
天笠, 俊之
アマガサ, トシユキ
AMAGASA, Toshiyuki
北川, 博之
キタガワ, ヒロユキ
KITAGAWA, Hiroyuki
Bou, Savong
Keyword search over relational streams is useful when allowing users to query on streams without understanding the details about the streams and query language as well. There have been several research works on this direction, and the state-of-the-art approaches exploit Candidate Networks (CNs), which are schema-level descriptions of possible joining networks of tuples, and generate query plans based on CNs. However, in fact, the performance of these approaches seriously degrades in particular when the maximum size of CNs () and/or the number of query keywords are large due to the explosive increase in the number of CNs. To cope with this problem, we propose a novel query plan called MX-structure to consolidate CNs as much as possible. We suppress explosive blowup of nodes in query plans by consolidating all common edges among CNs. The experimental results prove that the proposed algorithm performs much better than the state-of-the-art approaches.
journal article
Elsevier
2019-03
application/pdf
Information systems
81
117
135
03064379
AA00227103
https://tsukuba.repo.nii.ac.jp/record/51833/files/IS_81-117.pdf
eng
10.1016/j.is.2018.12.004
©2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/