Integrating Background Knowledge Into Text Classification

Zelikovitz, Sarah; Hirsh, Haym

Integrating Background Knowledge Into Text Classification

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Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 1448-1448.

Abstract

We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of training examples. The second method uses background knowledge to reexpress the training examples. The last method treats pieces of background knowledge as unlabeled examples, and actually classifies them. The choice of background knowledge affects each method's performance and we discuss which type of background knowledge is most useful for each specific method.

Sarah Zelikovitz, and Haym Hirsh. 2003. Integrating Background Knowledge Into Text Classification. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03. IJCAI, 1448–1448. https://ijcai.org/proceedings/2003/232

@inproceedings{ijcai2003p232,
  title     = {Integrating Background Knowledge Into Text Classification},
  author    = {Zelikovitz, Sarah and Hirsh, Haym},
  booktitle = {Proceedings of the Eighteenth International Joint Conference on
               Artificial Intelligence, {IJCAI-03}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Georg Gottlob},
  pages     = {1448--1448},
  year      = {2003},
  url       = {https://ijcai.org/proceedings/2003/232},
}

TY  - CPAPER
TI  - Integrating Background Knowledge Into Text Classification
AU  - Zelikovitz, Sarah
AU  - Hirsh, Haym
T2  - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2003
SP  - 1448
EP  - 1448
UR  - https://ijcai.org/proceedings/2003/232
ER  -