Improving text classification by using encyclopedia knowledge

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Improving text classification by using encyclopedia knowledge is a 2007 conference paper written in English by Wang P., Hu J., Zeng H.-J., Chen L., Chen Z. and published in Proceedings - IEEE International Conference on Data Mining, ICDM.

[edit] Abstract

The exponential growth of text documents available on the Internet has created an urgent need for accurate, fast, and general purpose text classification algorithms. However, the "bag of words" representation used for these classification methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. In order to deal with this problem, we integrate background knowledge - in our application: Wikipedia - into the process of classifying text documents. The experimental evaluation on Reuters newsfeeds and several other corpus shows that our classification results with encyclopedia knowledge are much better than the baseline "bag of words" methods.

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