Abstractive Multi-Document Summarization based on Semantic Link Network

Wei Li, Hai Zhuge

Research output: Contribution to journalArticlepeer-review


The key to realize advanced document summarization is semantic representation of documents. This paper investigates the role of Semantic Link Network in representing and understanding documents for multi-document summarization. It proposes a novel abstractive multi-document summarization framework by first transforming documents into a Semantic Link Network of concepts and events and then transforming the Semantic Link Network into the summary of the documents based on the selection of important concepts and events while keeping semantics coherence. Experiments on benchmark datasets show that the proposed summarization approach significantly outperforms relevant state-of-the-art baselines and the Semantic Link Network plays an important role in representing and understanding documents.
Original languageEnglish
JournalIEEE Transactions on Knowledge and Data Engineering
Early online date14 Jun 2019
Publication statusE-pub ahead of print - 14 Jun 2019

Bibliographical note

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  • Abstractive Summarization
  • Information Extraction
  • Multi-Document Summarization
  • Semantic Link Network


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