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Answering aggregate keyword queries on relational databases using minimal group-bys

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Jian PeiAuthors Info & Claims

EDBT '09: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology

Pages 108 - 119

https://doi.org/10.1145/1516360.1516374

Published: 24 March 2009 Publication History

Abstract

Keyword search has been recently extended to relational databases to retrieve information from text-rich attributes. However, all the existing methods focus on finding individual tuples matching a set of query keywords from one table or the join of multiple tables. In this paper, we motivate a novel problem of aggregate keyword search: finding minimal group-bys covering a set of query keywords well, which is useful in many applications. We develop two interesting approaches to tackle the problem, and further extend our methods to allow partial matches. An extensive empirical evaluation using both real data sets and synthetic data sets is reported to verify the effectiveness of aggregate keyword search and the efficiency of our methods.

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Cited By

Chen Z(2015)Towards Integrated Study of Data Management and Data MiningProcedia Computer Science10.1016/j.procs.2015.07.11755(1331-1339)Online publication date: 2015
https://doi.org/10.1016/j.procs.2015.07.117
Ribeiro JBelo O(2014)Pocket-cubes, bringing multidimensional data views to mobile platforms2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC.2014.6974481(3555-3560)Online publication date: Oct-2014
https://doi.org/10.1109/SMC.2014.6974481
Hu HZhang MHe ZWang PWang WLiu C(2014)Topical Presentation of Search Results on DatabaseDatabase Systems for Advanced Applications10.1007/978-3-319-05813-9_23(343-360)Online publication date: 2014
https://doi.org/10.1007/978-3-319-05813-9_23
Show More Cited By

Answering aggregate keyword queries on relational databases using minimal group-bys
1. Information systems
  1. Data management systems
    1. Database management system engines
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory

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cover image ACM Other conferences

EDBT '09: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology

March 2009

1180 pages

ISBN:9781605584225

DOI:10.1145/1516360

Editors:
Martin Kersten
CWI, The Netherlands
,
Boris Novikov
University of Saint Petersburg, Russia
,
Jens Teubner
ETH Zurich, Switzerland
,
Vladimir Polutin
HP Labs, Russia
,
Stefan Manegold
CWI, The Netherlands

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 March 2009

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EDBT/ICDT '09

EDBT/ICDT '09: EDBT/ICDT '09 joint conference

March 24 - 26, 2009

Saint Petersburg, Russia

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Overall Acceptance Rate 7 of 10 submissions, 70%

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Cited By

Chen Z(2015)Towards Integrated Study of Data Management and Data MiningProcedia Computer Science10.1016/j.procs.2015.07.11755(1331-1339)Online publication date: 2015
https://doi.org/10.1016/j.procs.2015.07.117
Ribeiro JBelo O(2014)Pocket-cubes, bringing multidimensional data views to mobile platforms2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC.2014.6974481(3555-3560)Online publication date: Oct-2014
https://doi.org/10.1109/SMC.2014.6974481
Hu HZhang MHe ZWang PWang WLiu C(2014)Topical Presentation of Search Results on DatabaseDatabase Systems for Advanced Applications10.1007/978-3-319-05813-9_23(343-360)Online publication date: 2014
https://doi.org/10.1007/978-3-319-05813-9_23
Park JLee S(2013)A graph-theoretic approach to optimize keyword queries in relational databasesKnowledge and Information Systems10.1007/s10115-013-0690-241:3(843-870)Online publication date: 16-Oct-2013
https://doi.org/10.1007/s10115-013-0690-2
Li LPetschulat STang GPei JLuk W(2012)Efficient and Effective Aggregate Keyword Search on Relational DatabasesInternational Journal of Data Warehousing and Mining10.4018/jdwm.20121001038:4(41-81)Online publication date: 1-Oct-2012
https://dl.acm.org/doi/10.4018/jdwm.2012100103
Chen L(2012)An Automatic Machine Learning Method for the Study of Keyword SuggestionMachine Learning Algorithms for Problem Solving in Computational Applications10.4018/978-1-4666-1833-6.ch009(149-165)Online publication date: 2012
https://doi.org/10.4018/978-1-4666-1833-6.ch009
Qin LYu JChang L(2012)Computing Structural Statistics by Keywords in DatabasesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2012.7824:10(1731-1746)Online publication date: 1-Oct-2012
https://dl.acm.org/doi/10.1109/TKDE.2012.78
Chen L(2012)Building a term suggestion and ranking system based on a probabilistic analysis model and a semantic analysis graphDecision Support Systems10.1016/j.dss.2012.02.00153:1(257-266)Online publication date: 1-Apr-2012
https://dl.acm.org/doi/10.1016/j.dss.2012.02.001
Zhao BLin XDing BHan J(2011)TEXplorerProceedings of the 20th ACM international conference on Information and knowledge management10.1145/2063576.2063822(1709-1718)Online publication date: 24-Oct-2011
https://dl.acm.org/doi/10.1145/2063576.2063822
Ding BZhao BLin CHan JZhai CSrivastava AOza N(2011)Efficient Keyword-Based Search for Top-K Cells in Text CubeIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2011.3423:12(1795-1810)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1109/TKDE.2011.34
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