Online citations, reference lists, and bibliographies.
← Back to Search

An Improved Method Of Keyword Search Over Relational Data Streams By Aggressive Candidate Network Consolidation

Savong Bou, T. Amagasa, H. Kitagawa
Published 2016 · Computer Science

Save to my Library
Download PDF
Analyze on Scholarcy Visualize in Litmaps
Share
Reduce the time it takes to create your bibliography by a factor of 10 by using the world’s favourite reference manager
Time to take this seriously.
Get Citationsy
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 $$T_{max}$$ and/or the number of query keywords are large due to the explosive increase in number of CNs. To cope with this problem, we propose a novel query plan called MX-structure to consolidate all 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.
This paper references
DTL's DataSpot: Database Exploration Using Plain Language
Shaul Dar (1998)
10.1109/ICDE.2002.994693
DBXplorer: a system for keyword-based search over relational databases
S. Agrawal (2002)
10.1016/B978-155860869-6/50065-2
DISCOVER: Keyword Search in Relational Databases
V. Hristidis (2002)
10.1145/564691.564782
DBXplorer: enabling keyword search over relational databases
S. Agrawal (2002)
10.1016/B978-012722442-8/50080-X
Efficient IR-Style Keyword Search over Relational Databases
V. Hristidis (2003)
10.1007/978-3-540-24607-7_1
CQL: A Language for Continuous Queries over Streams and Relations
A. Arasu (2003)
10.1016/B978-012088469-8.50078-4
Probabilistic Ranking of Database Query Results
S. Chaudhuri (2004)
10.1145/1247480.1247548
Keyword search on relational data streams
A. Markowetz (2007)
10.1109/ISORC.2008.25
Cyber Physical Systems: Design Challenges
Edward A. Lee (2008)
10.1007/s00778-010-0190-x
Scalable keyword search on large data streams
Lu Qin (2009)
10.1007/978-3-642-29035-0_5
Scalable Top-k Keyword Search in Relational Databases
Yanwei Xu (2012)
10.1109/ICDE.2015.7113302
Meaningful keyword search in relational databases with large and complex schema
M. Kargar (2015)
10.1007/978-3-319-15705-4_22
Agent-Based M&S of Smart Sensors for Knowledge Acquisition Inside the Internet of Things and Sensor Networks
Michal Dyk (2015)
10.1109/ICDE.2015.7113301
Ranking Candidate Networks of relations to improve keyword search over relational databases
P. D. Oliveira (2015)
On the Diagnosis of Cyber-Physical Production Systems
O. Niggemann (2015)
10.1007/978-3-319-15705-4_49
Experience-Oriented Enhancement of Smartness For Internet of Things
Haoxi Zhang (2015)
10.1007/978-3-540-28608-0_16
STREAM: The Stanford Data Stream Management System
A. Arasu (2016)



This paper is referenced by
Semantic Scholar Logo Some data provided by SemanticScholar