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» Learning from Labeled and Unlabeled Data Using Random Walks
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KDD
2009
ACM
211views Data Mining» more  KDD 2009»
14 years 8 months ago
Address standardization with latent semantic association
Address standardization is a very challenging task in data cleansing. To provide better customer relationship management and business intelligence for customer-oriented cooperates...
Honglei Guo, Huijia Zhu, Zhili Guo, Xiaoxun Zhang,...
RSS
2007
198views Robotics» more  RSS 2007»
13 years 9 months ago
CRF-Matching: Conditional Random Fields for Feature-Based Scan Matching
— Matching laser range scans observed at different points in time is a crucial component of many robotics tasks, including mobile robot localization and mapping. While existing t...
Fabio T. Ramos, Dieter Fox, Hugh F. Durrant-Whyte
ECCV
2010
Springer
13 years 11 months ago
Automatic Learning of Background Semantics in Generic Surveilled Scenes
Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analy...
Carles Fernández, Jordi Gonzàlez, Xavier Roca
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
14 years 8 months ago
Extracting discriminative concepts for domain adaptation in text mining
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
Bo Chen, Wai Lam, Ivor Tsang, Tak-Lam Wong
ACL
2009
13 years 5 months ago
A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge
Sentiment classification refers to the task of automatically identifying whether a given piece of text expresses positive or negative opinion towards a subject at hand. The prolif...
Tao Li, Yi Zhang 0005, Vikas Sindhwani