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» CURE: An Efficient Clustering Algorithm for Large Databases
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KDD
2006
ACM
160views Data Mining» more  KDD 2006»
16 years 3 months ago
Coherent closed quasi-clique discovery from large dense graph databases
Frequent coherent subgraphscan provide valuable knowledgeabout the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large...
Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Ka...
156
Voted
CORR
2010
Springer
219views Education» more  CORR 2010»
15 years 3 months ago
Finding Sequential Patterns from Large Sequence Data
Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mini...
Mahdi Esmaeili, Fazekas Gabor
143
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BMCBI
2010
149views more  BMCBI 2010»
15 years 3 months ago
KID - an algorithm for fast and efficient text mining used to automatically generate a database containing kinetic information o
Background: The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger ...
Stephanie Heinen, Bernhard Thielen, Dietmar Schomb...
ACL
2008
15 years 4 months ago
Distributed Word Clustering for Large Scale Class-Based Language Modeling in Machine Translation
In statistical language modeling, one technique to reduce the problematic effects of data sparsity is to partition the vocabulary into equivalence classes. In this paper we invest...
Jakob Uszkoreit, Thorsten Brants
117
Voted
SSDBM
2000
IEEE
87views Database» more  SSDBM 2000»
15 years 7 months ago
A Tool for Nesting and Clustering Large Objects
In implementations of non-standard database systems, large objects are often embedded within an aggregate of different types, i.e. a tuple. For a given size and access probabilit...
Stefan Dieker, Ralf Hartmut Güting, Miguel Ro...