A web text classification technique for unlabeled training samples

@article{Tchiegue2015AWT,
  title={A web text classification technique for unlabeled training samples},
  author={Francois Tchiegue and Rui Li and ShiLong Ma},
  journal={2015 6th IEEE International Conference on Software Engineering and Service Science (ICSESS)},
  year={2015},
  pages={437-440}
}
The common classification is conducted under the supervised learning algorithms, which design classifiers through learning the labeled training samples. However, in actual situations, it is very costly to acquire class-labeled samples, because manually labeling documents requires a lot of time and efforts from experts. Therefore, it restrains the text classification to a great extent. To solve the issue that labeled texts are hard to retrieve from the Internet, this paper has proposed the text… CONTINUE READING

References

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

Density based clustering." Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

Kriegel, Hans Peter
  • 2011
VIEW 1 EXCERPT

A survey of clustering data mining techniques." Grouping multidimensional data

Berkhin, Pavel
  • 2006
VIEW 1 EXCERPT

Recent advances in clustering: A brief survey.

Kotsiantis, Sotiris, Panayiotis Pintelas
  • WSEAS Transactions on Information Science and Applications
  • 2004
VIEW 1 EXCERPT

Raftery . " How many clusters ? Which clustering method ? Answers via model - based cluster analysis

E. Adrian
  • 1997