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KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 9 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
14 years 9 months ago
Mining broad latent query aspects from search sessions
Search queries are typically very short, which means they are often underspecified or have senses that the user did not think of. A broad latent query aspect is a set of keywords ...
Xuanhui Wang, Deepayan Chakrabarti, Kunal Punera
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 9 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
14 years 9 months ago
A multi-relational approach to spatial classification
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
Richard Frank, Martin Ester, Arno Knobbe
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
14 years 9 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