Cross-domain classification: Trade-off between complexity and accuracy

@article{Lex2009CrossdomainCT,
  title={Cross-domain classification: Trade-off between complexity and accuracy},
  author={Elisabeth Lex and Christin Seifert and Michael Granitzer and Andreas Juffinger},
  journal={2009 International Conference for Internet Technology and Secured Transactions, (ICITST)},
  year={2009},
  pages={1-6}
}
Text classification is one of the core applications in data mining due to the huge amount of not categorized digital data available. Training a text classifier generates a model that reflects the characteristics of the domain. However, if no training data is available, labeled data from a related but different domain might be exploited to perform cross-domain classification. In our work, we aim to accurately classify unlabeled blogs into commonly agreed newspaper categories using labeled data… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 16 REFERENCES

Similar Papers

Loading similar papers…