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KDD
2008
ACM
128views Data Mining» more  KDD 2008»
14 years 10 months ago
Scaling up text classification for large file systems
: We combine the speed and scalability of information retrieval with the generally superior classification accuracy offered by machine learning, yielding a two-phase text classifie...
George Forman, Shyamsundar Rajaram
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
14 years 10 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih
KDD
2006
ACM
167views Data Mining» more  KDD 2006»
14 years 10 months ago
Identifying "best bet" web search results by mining past user behavior
The top web search result is crucial for user satisfaction with the web search experience. We argue that the importance of the relevance at the top position necessitates special h...
Eugene Agichtein, Zijian Zheng
KDD
2006
ACM
149views Data Mining» more  KDD 2006»
14 years 10 months ago
Regularized discriminant analysis for high dimensional, low sample size data
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Jieping Ye, Tie Wang
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
14 years 10 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler