Sciweavers

1768 search results - page 15 / 354
» Mining Very Large Databases
Sort
View
SIGMOD
2009
ACM
192views Database» more  SIGMOD 2009»
14 years 10 months ago
Scalable join processing on very large RDF graphs
With the proliferation of the RDF data format, engines for RDF query processing are faced with very large graphs that contain hundreds of millions of RDF triples. This paper addre...
Thomas Neumann, Gerhard Weikum
VLDB
2004
ACM
119views Database» more  VLDB 2004»
14 years 10 months ago
Evaluating holistic aggregators efficiently for very large datasets
Indatawarehousingapplications,numerousOLAP queries involve the processing of holistic aggregators such as computing the "top n," median, quantiles, etc. In this paper, we...
Lixin Fu, Sanguthevar Rajasekaran
KDD
2001
ACM
150views Data Mining» more  KDD 2001»
14 years 2 months ago
Mining top-n local outliers in large databases
Wen Jin, Anthony K. H. Tung, Jiawei Han
SIGMOD
1998
ACM
99views Database» more  SIGMOD 1998»
14 years 2 months ago
CURE: An Efficient Clustering Algorithm for Large Databases
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim
BDA
2000
13 years 11 months ago
Incremental Mining of Sequential Patterns in Large Databases
In this paper we consider the problem of the incremental mining of sequential patterns when new transactions or new customers are added to an original database. We present a new a...
Florent Masseglia, Pascal Poncelet, Maguelonne Tei...