Revisiting UNLSumm: Improvement Through a Case Study
نویسندگان
چکیده
This paper presents some improvements that have been made to UNLSumm, an automatic summarizer of UNL Texts. These are texts encoded in the Universal Networking Language (UNL), an artificial language intended to convey conceptualizations of natural language texts. In UNLSumm, a set of heuristics is responsible for, based in the UNL characteristics, prune sentences of a UNL Text, generating its UNL summary. We now present a case study conducted to identify possible bad heuristics and approaches, and also the improvements made to the summarization model based on such a study.
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