A machine learning approach to sentence ordering for multidocument summarization and its evaluation

Danushka Bollegala*, Naoaki Okazaki, Mitsuru Ishizuka

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Ordering information is a difficult but a important task for natural language generation applications. A wrong order of information not only makes it difficult to understand, but also conveys an entirely different idea to the reader. This paper proposes an algorithm that learns orderings from a set of human ordered texts. Our model consists of a set of ordering experts. Each expert gives its precedence preference between two sentences. We combine these preferences and order sentences. We also propose two new metrics for the evaluation of sentence orderings. Our experimental results show that the proposed algorithm outperforms the existing methods in all evaluation metrics.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages624-635
Number of pages12
Volume3651 LNAI
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event2nd International Joint Conference on Natural Language Processing, IJCNLP 2005 - Jeju Island
Duration: 2005 Oct 112005 Oct 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3651 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Joint Conference on Natural Language Processing, IJCNLP 2005
CityJeju Island
Period05/10/1105/10/13

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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