Choosing the Best Comparison Under the Circumstances
نویسنده
چکیده
The Methodius Natural Language Generation systems generates personalized descriptions of objects from a collection. As part of the user modeling component, it creates comparisons between the current object being viewed and previous objects from the user history. We present our general algorithm for choosing the best comparison, which can be optimized to give the best result for different domains through a parameterizable scoring function.
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