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» Practical Preference Relations for Large Data Sets
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SIGMOD
2002
ACM
134views Database» more  SIGMOD 2002»
16 years 5 months ago
Wavelet synopses with error guarantees
Recent work has demonstrated the effectiveness of the wavelet decomposition in reducing large amounts of data to compact sets of wavelet coefficients (termed "wavelet synopse...
Minos N. Garofalakis, Phillip B. Gibbons
EDBT
2012
ACM
247views Database» more  EDBT 2012»
13 years 7 months ago
Heuristics-based query optimisation for SPARQL
Query optimization in RDF Stores is a challenging problem as SPARQL queries typically contain many more joins than equivalent relational plans, and hence lead to a large join orde...
Petros Tsialiamanis, Lefteris Sidirourgos, Irini F...
RECOMB
2011
Springer
14 years 8 months ago
Rich Parameterization Improves RNA Structure Prediction
Motivation. Current approaches to RNA structure prediction range from physics-based methods, which rely on thousands of experimentally-measured thermodynamic parameters, to machin...
Shay Zakov, Yoav Goldberg, Michael Elhadad, Michal...
KDD
2012
ACM
247views Data Mining» more  KDD 2012»
13 years 7 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
ML
2006
ACM
15 years 5 months ago
Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. A common way to measure performance in these domains is to use precision and recall i...
Mark Goadrich, Louis Oliphant, Jude W. Shavlik