Detecting Action Items in Multi-party Meetings: Annotation and Initial Experiments

  • Matthew Purver
  • Patrick Ehlen
  • John Niekrasz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4299)


This paper presents the results of initial investigation and experiments into automatic action item detection from transcripts of multi-party human-human meetings. We start from the flat action item annotations of [1], and show that automatic classification performance is limited. We then describe a new hierarchical annotation schema based on the roles utterances play in the action item assignment process, and propose a corresponding approach to automatic detection that promises improved classification accuracy while also enabling the extraction of useful information for summarization and reporting.


Action Item Task Description AAAI Spring Symposium Speak Language Understanding Speaker Utterance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Matthew Purver
    • 1
  • Patrick Ehlen
    • 1
  • John Niekrasz
    • 1
  1. 1.Center for the Study of Language and InformationStanford UniversityStanfordUSA

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