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KDD
2005
ACM
103views Data Mining» more  KDD 2005»
16 years 6 months ago
Robust boosting and its relation to bagging
Several authors have suggested viewing boosting as a gradient descent search for a good fit in function space. At each iteration observations are re-weighted using the gradient of...
Saharon Rosset
KDD
2005
ACM
135views Data Mining» more  KDD 2005»
16 years 6 months ago
A hybrid unsupervised approach for document clustering
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Mihai Surdeanu, Jordi Turmo, Alicia Ageno
195
Voted
KDD
2005
ACM
122views Data Mining» more  KDD 2005»
16 years 6 months ago
Pattern lattice traversal by selective jumps
Regardless of the frequent patterns to discover, either the full frequent patterns or the condensed ones, either closed or maximal, the strategy always includes the traversal of t...
Osmar R. Zaïane, Mohammad El-Hajj
KDD
2004
ACM
148views Data Mining» more  KDD 2004»
16 years 6 months ago
Fast discovery of connection subgraphs
We define a connection subgraph as a small subgraph of a large graph that best captures the relationship between two nodes. The primary motivation for this work is to provide a pa...
Christos Faloutsos, Kevin S. McCurley, Andrew Tomk...
KDD
2004
ACM
160views Data Mining» more  KDD 2004»
16 years 6 months ago
Boosting for Text Classification with Semantic Features
Abstract. Current text classification systems typically use term stems for representing document content. Semantic Web technologies allow the usage of features on a higher semantic...
Stephan Bloehdorn, Andreas Hotho