Investigating automatic alignment methods for slide generation from academic papers

Brandon Beamer, Roxana Girju

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

Abstract

In this paper we investigate the task of automatic generation of slide presentations from academic papers, focusing initially on slide to paper alignment. We compare and evaluate four different alignment systems which utilize various combinations of methods used widely in other alignment and question answering approaches, such as TF-IDF term weighting and query expansion. Our best aligner achieves an accuracy of 75% and our findings show that for this application, average TF-IDF scoring performs more poorly than a simpler method based on the number of matched terms, and query expansion degrades aligner performance.

Original languageEnglish (US)
Title of host publication13th Conference on Computational Natural Language Learning
PublisherCoNLL
Pages111-119
Number of pages9
ISBN (Print)1932432299, 9781932432299
DOIs
StatePublished - 2009
Event13th Conference on Computational Natural Language Learning, CoNLL 2009 - Boulder, CO, United States
Duration: Jun 4 2009Jun 5 2009

Publication series

NameCoNLL 2009 - Proceedings of the Thirteenth Conference on Computational Natural Language Learning

Other

Other13th Conference on Computational Natural Language Learning, CoNLL 2009
CountryUnited States
CityBoulder, CO
Period6/4/096/5/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Linguistics and Language

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