Information as Basic for High-Precision Text Classification

  title={Information as Basic for High-Precision Text Classification},
  author={Ellen Riloff and Wendy G. Lehnert},
  journal={ACM Trans. Inf. Syst.},
We describe an approach to text classification that represents a compromise between traditional word-based techniques and in-depth natural language processing. Our approach uses a natural language processing task called “information extraction” as a basis for high-precision text classification. We present three algorithms that use varying amounts of extracted information to classify texts. The relevancy signatures algorithm uses linguistic phrases; the augmented relevancy signatures algorithm… CONTINUE READING


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