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    Coupled Hierarchical IR and Stochastic Models for Surface Information Extraction

    20th Annual BCS-IRSG Colloquium on IR

    Autrans, France. 25th - 27th March 1998


    H. Zaragoza & P. Gallinari


    We present in this paper a combination of Machine Learning based Information Retrieval (IR) techniques and stochastic language modelling in a hierarchical system that extracts surface information from text.

    At the lowest level of this hierarchy, documents and paragraphs are successively routed with IR techniques.

    At the top level, a stochastic language model extracts the most relevant phrases, and labels the type of information they contain.

    The approach and preliminary results are demonstrated on a subset of the MUC-6 Scenario Templates task.


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