Concept Learning for Cross-Domain Text Classification: A General Probabilistic Framework

@inproceedings{Zhuang2013ConceptLF,
  title={Concept Learning for Cross-Domain Text Classification: A General Probabilistic Framework},
  author={Fuzhen Zhuang and Ping Luo and Peifeng Yin and Qing He and Zhongzhi Shi},
  booktitle={IJCAI},
  year={2013}
}
Cross-domain learning targets at leveraging the knowledge from source domains to train accurate models for the test data from target domains with different but related data distributions. To tackle the challenge of data distribution difference in terms of raw features, previous works proposed to mine high-level concepts (e.g., word clusters) across data domains, which shows to be more appropriate for classification. However, all these works assume that the same set of concepts are shared in the… CONTINUE READING

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