Efficient keyword search over graph-structured data based on minimal covered r-cliques
Author:
Publisher
Zhejiang University Press
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing
Link
http://link.springer.com/content/pdf/10.1631/FITEE.1800133.pdf
Reference37 articles.
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2. Bergamaschi S, Guerra F, Interlandi M, et al., 2016. Combining user and database perspective for solving keyword queries over relational databases. Inform Syst, 55: 1–19. https://doi.org/10.1016/j.is.2015.07.005
3. Bron C, Kerbosch J, 1973. Finding all cliques of an undirected graph. Commun ACM, 16(9): 575–577. https://doi.org/10.1145/362342.362367
4. Calado P, da Silva AS, Laender AHF, et al., 2004. A Bayesian network approach to searching Web databases through keyword-based queries. Inform Process Manag, 40(5): 773–790. https://doi.org/10.10167/j.ipm.2004.03.002
5. Dasari NS, Ranjan D, Mohammad Z, 2014. Maximal clique enumeration for large graphs on Hadoop framework. Proc 1st Workshop on Parallel Programming for Analytics Applications, p.21–30. https://doi.org/10.1145/2567634.2567640
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