Using Integer Linear Programming for Content Selection, Lexicalization, and Aggregation to Produce Compact Texts from OWL Ontologies
نویسندگان
چکیده
We present an Integer Linear Programming model of content selection, lexicalization, and aggregation that we developed for a system that generates texts from OWL ontologies. Unlike pipeline architectures, our model jointly considers the available choices in these three text generation stages, to avoid greedy decisions and produce more compact texts. Experiments with two ontologies confirm that it leads to more compact texts, compared to a pipeline with the same components, with no deterioration in the perceived quality of the generated texts. We also present an approximation of our model, which allows longer texts to be generated efficiently.
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