Web News Multi-document Summarization Based on Event Extraction

TLDR: The event extraction technology is introduced and an event extraction based web news multi-document summarization method is proposed, which improves summarization quality significantly.

Abstract: State-of-the-art automatic summarization is based on text segment clustering to avoid redundancy defects in the traditional approachesBut some of the text segments in the web news are irrelevant to the subject,which affects the result of clustering and damages the conciseness of summarizationThis paper introduces the event extraction technology and proposes an event extraction based web news multi-document summarization methodFirstly,the method distinguishes event and non-event from the news through a binary classifierThen,the original documents' physical division based on paragraphs or sentences are transformed into event based content logical division through clusteringFinally,the summarization is derived from the extraction,taxis and embellishment of the major eventsExperimental results demonstrate the effectiveness of the proposed method,which improves summarization quality significantly