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» Efficient Correlation Search from Graph Databases
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SIGMOD
2008
ACM
214views Database» more  SIGMOD 2008»
15 years 9 months ago
A graph method for keyword-based selection of the top-K databases
While database management systems offer a comprehensive solution to data storage, they require deep knowledge of the schema, as well as the data manipulation language, in order to...
Quang Hieu Vu, Beng Chin Ooi, Dimitris Papadias, A...
93
Voted
EDBT
2009
ACM
277views Database» more  EDBT 2009»
15 years 2 months ago
G-hash: towards fast kernel-based similarity search in large graph databases
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
Xiaohong Wang, Aaron M. Smalter, Jun Huan, Gerald ...
JCP
2008
171views more  JCP 2008»
14 years 9 months ago
Mining Frequent Subgraph by Incidence Matrix Normalization
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Jia Wu, Ling Chen
104
Voted
BMCBI
2006
172views more  BMCBI 2006»
14 years 9 months ago
A novel scoring schema for peptide identification by searching protein sequence databases using tandem mass spectrometry data
Background: Tandem mass spectrometry (MS/MS) is a powerful tool for protein identification. Although great efforts have been made in scoring the correlation between tandem mass sp...
Zhuo Zhang, Shiwei Sun, Xiaopeng Zhu, Suhua Chang,...
SIGMOD
1997
ACM
148views Database» more  SIGMOD 1997»
15 years 1 months ago
Beyond Market Baskets: Generalizing Association Rules to Correlations
One of the most well-studied problems in data mining is mining for association rules in market basket data. Association rules, whose significance is measured via support and confi...
Sergey Brin, Rajeev Motwani, Craig Silverstein