Rhetorics-based multi-document summarization

In this paper, a new multi-document summarization framework which combines rhetorical roles and corpus-based semantic analysis is proposed. The approach is able to capture the semantic and rhetorical relationships between sentences so as to combine them to produce coherent summaries. Experiments were conducted on datasets extracted from web-based news using standard evaluation methods. Results show the promise of our proposed model as compared to state-of-the-art approaches.

► We modeled a multi-document summarizer for information provided from web sources. ► The approach combines Natural-Language Processing, Discourse Models, and Machine Learning Techniques. ► CRF-based classifiers allow the model to deal with rhetorical knowledge in order to automatically generate coherent summaries. ► Experiments show promising results of rhetorical-based multi-document summarization when compared with traditional methods.