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» Predicting query performance on the web
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94
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ER
2004
Springer
163views Database» more  ER 2004»
15 years 1 months ago
From Ontology to Relational Databases
The semantic web envisions a World Wide Web in which data is described with rich semantics and applications can pose complex queries. Ontologies, a cornerstone of the semantic web,...
Anuradha Gali, Cindy X. Chen, Kajal T. Claypool, R...
190
Voted
ISBRA
2011
Springer
14 years 1 months ago
Query-Adaptive Ranking with Support Vector Machines for Protein Homology Prediction
Abstract. Protein homology prediction is a crucial step in templatebased protein structure prediction. The functions that rank the proteins in a database according to their homolog...
Yan Fu, Rong Pan, Qiang Yang, Wen Gao
EDBT
2011
ACM
199views Database» more  EDBT 2011»
14 years 1 months ago
Predicting completion times of batch query workloads using interaction-aware models and simulation
A question that database administrators (DBAs) routinely need to answer is how long a batch query workload will take to complete. This question arises, for example, while planning...
Mumtaz Ahmad, Songyun Duan, Ashraf Aboulnaga, Shiv...
CLOUD
2010
ACM
15 years 2 months ago
The case for PIQL: a performance insightful query language
Large-scale, user-facing applications are increasingly moving from relational databases to distributed key/value stores for high-request-rate, low-latency workloads. Often, this m...
Michael Armbrust, Nick Lanham, Stephen Tu, Armando...
71
Voted
SIGMOD
2010
ACM
187views Database» more  SIGMOD 2010»
15 years 2 months ago
PIQL: a performance insightful query language
Large-scale websites are increasingly moving from relational databases to distributed key-value stores for high request rate, low latency workloads. Often this move is motivated n...
Michael Armbrust, Stephen Tu, Armando Fox, Michael...