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» CURE: An Efficient Clustering Algorithm for Large Databases
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DMKD
1997
ACM
308views Data Mining» more  DMKD 1997»
15 years 3 months ago
A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
Zhexue Huang
SIGMOD
1999
ACM
183views Database» more  SIGMOD 1999»
15 years 4 months ago
OPTICS: Ordering Points To Identify the Clustering Structure
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysi...
Mihael Ankerst, Markus M. Breunig, Hans-Peter Krie...
BMCBI
2007
177views more  BMCBI 2007»
14 years 11 months ago
The BioPrompt-box: an ontology-based clustering tool for searching in biological databases
Background: High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This sc...
Claudio Corsi, Paolo Ferragina, Roberto Marangoni
HT
1991
ACM
15 years 3 months ago
Implementing Hypertext Database Relationships through Aggregations and Exceptions
In order to combine hypertext with database facilities, we show how to extract an effective storage structure from given instance relationships. The schema of the structure recogn...
Yoshinori Hara, Arthur M. Keller, Gio Wiederhold
DAWAK
1999
Springer
15 years 3 months ago
Implementation of Multidimensional Index Structures for Knowledge Discovery in Relational Databases
Efficient query processing is one of the basic needs for data mining algorithms. Clustering algorithms, association rule mining algorithms and OLAP tools all rely on efficient quer...
Stefan Berchtold, Christian Böhm, Hans-Peter ...