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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 7 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
KDD
2004
ACM
148views Data Mining» more  KDD 2004»
16 years 7 months ago
Spying Out Accurate User Preferences for Search Engine Adaptation
Abstract. Most existing search engines employ static ranking algorithms that do not adapt to the specific needs of users. Recently, some researchers have studied the use of clickth...
Lin Deng, Wilfred Ng, Xiaoyong Chai, Dik Lun Lee
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
16 years 7 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
KDD
2002
ACM
170views Data Mining» more  KDD 2002»
16 years 7 months ago
Enhanced word clustering for hierarchical text classification
In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering&...
Inderjit S. Dhillon, Subramanyam Mallela, Rahul Ku...
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 7 months ago
Transforming data to satisfy privacy constraints
Data on individuals and entities are being collected widely. These data can contain information that explicitly identifies the individual (e.g., social security number). Data can ...
Vijay S. Iyengar
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