Multi-document summarization (MDS) systems have been designed for short, unstructured summaries of 10-15 documents, and are inadequate for larger document collections. We propose a new approach to scaling up summarization called hierarchical summarization, and present the first implemented system, SUMMA. SUMMA produces a hierarchy of relatively short summaries, in which the top level provides a general overview and users can navigate the hierarchy to drill down for more details on topics of interest. SUMMA optimizes for coherence as well as coverage of salient information. In an Amazon Mechanical Turk evaluation, users prefered SUMMA ten times as often as flat MDS and three times as often as timelines.
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Hierarchical Summarization: Scaling Up Multi-Document Summarization
Semantic Scholar · Computer Science · 2014
Abstract
Multi-document summarization (MDS) systems have been designed for short, unstructured summaries of 10-15 documents, and are inadequate for larger document collections. We propose a new approach to scaling up summarization called hierarchical summarization, and present the first implemented system, SUMMA. SUMMA produces a hierarchy of relatively short summaries, in which the top level provides a general overview and users can navigate the hierarchy to drill down for more details on topics of interest. SUMMA optimizes for coherence as well as coverage of salient information. In an Amazon Mechanical Turk evaluation, users prefered SUMMA ten times as often as flat MDS and three times as often as timelines.