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SIGMOD
2004
ACM
140views Database» more  SIGMOD 2004»
14 years 4 months ago
Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Corrine Cheng, Jörg Sander, Samer Nassar
KDD
2000
ACM
101views Data Mining» more  KDD 2000»
13 years 8 months ago
Incremental quantile estimation for massive tracking
Data--call records, internet packet headers, or other transaction records--are coming down a pipe at a ferocious rate, and we need to monitor statistics of the data. There is no r...
Fei Chen, Diane Lambert, José C. Pinheiro
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 5 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson