Supervised Learning of Automatic Pyramid for Optimization-Based Multi-Document Summarization

Abstract

We present a new supervised framework that learns to estimate automatic Pyramid scores and uses them for optimizationbased extractive multi-document summarization. For learning automatic Pyramid scores, we developed a method for automatic training data generation which is based on a genetic algorithm using automatic Pyramid as the fitness function. Our… (More)
DOI: 10.18653/v1/P17-1100

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