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This paper describes a pilot version of a commercial application of natural language processing techniques to the problem of categorizing news stories into broad topic categories. The system does not perform a complete semantic or syntactic analyses of the input stories. Its categorizations are dependent on fragmentary recognition using patternmatching techniques. The fragments it looks for are determined by a set of knowledge-based rules. The accuracy of the system is only slightly lower than that of human categorizers.

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