On macro- and micro-level information in multiple documents and its influence on summarization

  • Authors:

  • Jiaming Zhan;Han Tong Loh;Ying Liu

  • Affiliations:

  • Department of Mechanical Engineering, National University of Singapore, Singapore 119260, Singapore;Department of Mechanical Engineering, National University of Singapore, Singapore 119260, Singapore;Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China

  • Venue:
  • International Journal of Information Management: The Journal for Information Professionals
  • Year:
  • 2009

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Abstract

A well-known challenge for multi-document summarization (MDS) is that a single best or ''gold standard'' summary does not exist, i.e. it is often difficult to secure a consensus among reference summaries written by different authors. It therefore motivates us to study what the ''important information'' is in multiple input documents that will guide different authors in writing a summary. In this paper, we propose the notions of macro- and micro-level information. Macro-level information refers to the salient topics shared among different input documents, while micro-level information consists of different sentences that act as elaborating or provide complementary details for those salient topics. Experimental studies were conducted to examine the influence of macro- and micro-level information on summarization and its evaluation. Results showed that human subjects highly relied on macro-level information when writing a summary. The length allowed for summaries is the leading factor that affects the summary agreement. Meanwhile, our summarization evaluation approach based on the proposed macro- and micro-structure information also suggested that micro-level information offered complementary details for macro-level information. We believe that both levels of information form the ''important information'' which affects the modeling and evaluation of automatic summarization systems.