Question Answering System with Fine Grain Answer Types and Search Refinement
نویسنده
چکیده
In the present paper, we describe the improvement of our Question Answering System (QAS). We added keywords relevance factor, search refinement and fine grain type extraction of the expected answer to the system. We attempted to avoid using heavy natural language processing techniques in order to process large amounts of data from the newspaper corpus database. These changes have yielded promising experimental results. These changes and the experimental results are detailed herein.
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تاریخ انتشار 2005