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» Very Large Databases: How Large, How Different
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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 1 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
VLDB
1998
ACM
312views Database» more  VLDB 1998»
14 years 22 days ago
WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases
Many applications require the management of spatial data. Clustering large spatial databases is an important problem which tries to find the densely populated regions in the featu...
Gholamhosein Sheikholeslami, Surojit Chatterjee, A...
P2P
2007
IEEE
104views Communications» more  P2P 2007»
14 years 2 months ago
How stable are large superpeer networks against attack?
In this paper, we analyze the stability of large scale superpeer networks against attacks. Two different kinds of attacks namely deterministic and degree dependent attack have bee...
Bivas Mitra, Sujoy Ghose, Niloy Ganguly
TRIDENTCOM
2010
IEEE
13 years 6 months ago
How to Build Complex, Large-Scale Emulated Networks
Abstract. This paper describes AutoNetkit, an auto-configuration tool for complex network emulations using Netkit, allowing large-scale networks to be tested on commodity hardware....
Hung X. Nguyen, Matthew Roughan, Simon Knight, Nic...
ACL
1998
13 years 10 months ago
How Verb Subcategorization Frequencies Are Affected By Corpus Choice
The probabilistic relation between verbs and their arguments plays an important role in modern statistical parsers and supertaggers, and in psychological theories of language proc...
Douglas Roland, Daniel Jurafsky