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» Mining Very Large Databases
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VLDB
2005
ACM
177views Database» more  VLDB 2005»
15 years 8 months ago
Discovering Large Dense Subgraphs in Massive Graphs
We present a new algorithm for finding large, dense subgraphs in massive graphs. Our algorithm is based on a recursive application of fingerprinting via shingles, and is extreme...
David Gibson, Ravi Kumar, Andrew Tomkins
130
Voted
PR
2008
117views more  PR 2008»
15 years 3 months ago
A scale-free distribution of false positives for a large class of audio similarity measures
The "bag-of-frames" approach (BOF) to audio pattern recognition models signals as the long-term statistical distribution of their local spectral features, a prototypical...
Jean-Julien Aucouturier, François Pachet
173
Voted
VLDB
2002
ACM
154views Database» more  VLDB 2002»
15 years 3 months ago
I/O-Conscious Data Preparation for Large-Scale Web Search Engines
Given that commercial search engines cover billions of web pages, efficiently managing the corresponding volumes of disk-resident data needed to answer user queries quickly is a f...
Maxim Lifantsev, Tzi-cker Chiueh
KDD
1997
ACM
78views Data Mining» more  KDD 1997»
15 years 7 months ago
Mining Generalized Term Associations: Count Propagation Algorithm
We presenthere an approachand algorithm for mining generalizedterm associations.The problem is to find co-occurrencefrequenciesof terms, given a collection of documents eachwith r...
Jonghyun Kahng, Wen-Hsiang Kevin Liao, Dennis McLe...
136
Voted
AUSAI
2004
Springer
15 years 7 months ago
Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining
Abstract. Association rule mining is a data mining technique that reveals interesting relationships in a database. Existing approaches employ different parameters to search for int...
Stefan Mutter, Mark Hall, Eibe Frank