One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from ...

In this paper we propose a domain adaptation method which directly minimizes both the distribution gap between the source domain and the target domain, as well ...

It makes the assumption that certain features are domain-specific while others are generalizable, or that there exist mappings from the original feature space ...

One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from ...

Sep 14, 2009 · Extracting Discriminative Concepts for Domain Adaptation in Text Mining. Published on Sep 14, 20093757 Views. Bo Chen. One common predictive ...

One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different ...

One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from ...

Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling · Extracting discriminative concepts for domain adaptation in text mining.

Domain Adaptation in NLP: Enhancing model performance in new domains by leveraging existing knowledge.

We present a novel approach to domain adaptation for text categorization, which merely requires that the source domain data are weakly annotated in the form ...