Exploiting Conceptual Relations of Sentences for Multi-document Summarization

Abstract

Multi-document Summarization becomes increasingly important in the age of big data. However, existing summarization systems do not or implicitly consider the conceptual relations of sentences. In this paper, we propose a novel method called Multi-document Summarization based on Explicit Semantics of Sentences (MDSES), which explicitly take conceptual relations of sentences into consideration. It is composed of three components: sentence-concept graph construction, concept clustering and summary generation. We first obtain sentence-concept semantic relation to construct a sentence-concept graph. Then we run graph weighting algorithm to get ranked weighted sentences and concepts. Besides, we obtain concept-concept semantic relation for concepts clustering to eliminate redundancy. Finally, we conduct summary generation to get informative summary. Experimental results on DUC dataset using ROUGE metrics demonstrate the good effectiveness of our methods.