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» Relational learning via latent social dimensions
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ICML
2004
IEEE
14 years 7 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
SDM
2011
SIAM
370views Data Mining» more  SDM 2011»
12 years 9 months ago
Sparse Latent Semantic Analysis
Latent semantic analysis (LSA), as one of the most popular unsupervised dimension reduction tools, has a wide range of applications in text mining and information retrieval. The k...
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G....
ACL
2011
12 years 10 months ago
Event Discovery in Social Media Feeds
We present a novel method for record extraction from social streams such as Twitter. Unlike typical extraction setups, these environments are characterized by short, one sentence ...
Edward Benson, Aria Haghighi, Regina Barzilay
CIKM
2009
Springer
13 years 11 months ago
Heterogeneous cross domain ranking in latent space
Traditional ranking mainly focuses on one type of data source, and effective modeling still relies on a sufficiently large number of labeled or supervised examples. However, in m...
Bo Wang, Jie Tang, Wei Fan, Songcan Chen, Zi Yang,...
HCI
2009
13 years 4 months ago
Antecedents of Attributions in an Educational Game for Social Learning: Who's to Blame?
Games are increasingly being used as educational tools, in part because they are presumed to enhance student motivation. We look at student motivation in games from the viewpoint o...
Amy Ogan, Vincent Aleven, Julia Kim, Christopher J...