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ICDM
2007
IEEE
183views Data Mining» more  ICDM 2007»
16 years 22 days ago
Depth-Based Novelty Detection and Its Application to Taxonomic Research
It is estimated that less than 10 percent of the world’s species have been described, yet species are being lost daily due to human destruction of natural habitats. The job of d...
Yixin Chen, Henry L. Bart Jr., Xin Dang, Hanxiang ...
KDD
1994
ACM
117views Data Mining» more  KDD 1994»
15 years 10 months ago
Application of the TETRAD II Program to the Study of Student Retention in U.S. Colleges
We applied TETRAD II, a causal discovery program developed in Carnegie Mellon University's Department of Philosophy, to a database containing information on 204 U.S. colleges...
Marek J. Druzdze, Clark Glymour
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 10 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
SDM
2004
SIAM
165views Data Mining» more  SDM 2004»
15 years 7 months ago
Visualizing RFM Segmentation
Segmentation based on RFM (Recency, Frequency, and Monetary) has been used for over 50 years by direct marketers to target a subset of their customers, save mailing costs, and imp...
Ron Kohavi, Rajesh Parekh
WWW
2010
ACM
15 years 6 months ago
Cross-domain sentiment classification via spectral feature alignment
Sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of users publishing sentiment data (e.g., reviews, blogs). Although traditio...
Sinno Jialin Pan, Xiaochuan Ni, Jian-Tao Sun, Qian...