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DOI: 10.4230/OASIcs.CMN.2014.154

Gathering Background Knowledge for Story Understanding through Crowdsourcing

Authors: Christos T. Rodosthenous and Loizos Michael

Published in: OASIcs, Volume 41, 2014 Workshop on Computational Models of Narrative

Abstract

Successfully comprehending stories involves integration of the story information with the reader's own background knowledge. A prerequisite, then, of building automated story understanding systems is the availability of such background knowledge. We take the approach that knowledge appropriate for story understanding can be gathered by sourcing the task to the crowd. Our methodology centers on breaking this task into a sequence of more specific tasks, so that human participants not only identify relevant knowledge, but also convert it into a machine-readable form, generalize it, and evaluate its appropriateness. These individual tasks are presented to human participants as missions in an online game, offering them, in this manner, an incentive for their participation. We report on an initial deployment of the game, and discuss our ongoing work for integrating the knowledge gathering task into a full-fledged story understanding engine.

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Christos T. Rodosthenous and Loizos Michael. Gathering Background Knowledge for Story Understanding through Crowdsourcing. In 2014 Workshop on Computational Models of Narrative. Open Access Series in Informatics (OASIcs), Volume 41, pp. 154-163, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{rodosthenous_et_al:OASIcs.CMN.2014.154,
  author =	{Rodosthenous, Christos T. and Michael, Loizos},
  title =	{{Gathering Background Knowledge for Story Understanding through Crowdsourcing}},
  booktitle =	{2014 Workshop on Computational Models of Narrative},
  pages =	{154--163},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-71-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{41},
  editor =	{Finlayson, Mark A. and Meister, Jan Christoph and Bruneau, Emile G.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2014.154},
  URN =		{urn:nbn:de:0030-drops-46537},
  doi =		{10.4230/OASIcs.CMN.2014.154},
  annote =	{Keywords: story understanding, knowledge representation, crowdsourcing, reasoning}
}

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DOI: 10.4230/OASIcs.CMN.2013.129

Narrative Similarity as Common Summary

Authors: Elektra Kypridemou and Loizos Michael

Published in: OASIcs, Volume 32, 2013 Workshop on Computational Models of Narrative

Abstract

The ability to identify similarities between narratives has been argued to be central in human interactions. Previous work that sought to formalize this task has hypothesized that narrative similarity can be equated to the existence of a common summary between the narratives involved. We offer tangible psychological evidence in support of this hypothesis. Human participants in our empirical study were presented with triples of stories, and were asked to rate: (i) the degree of similarity between story A and story B; (ii) the appropriateness of story C as a summary of story A; (iii) the appropriateness of story C as a summary of story B. The story triples were selected systematically to span the space of their possible interrelations. Empirical evidence gathered from this study overwhelmingly supports the position that the higher the latter two ratings are, the higher the first rating also is. Thus, while this work does not purport to formally define either of the two tasks involved, it does argue that one can be meaningfully reduced to the other.

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Elektra Kypridemou and Loizos Michael. Narrative Similarity as Common Summary. In 2013 Workshop on Computational Models of Narrative. Open Access Series in Informatics (OASIcs), Volume 32, pp. 129-146, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InProceedings{kypridemou_et_al:OASIcs.CMN.2013.129,
  author =	{Kypridemou, Elektra and Michael, Loizos},
  title =	{{Narrative Similarity as Common Summary}},
  booktitle =	{2013 Workshop on Computational Models of Narrative},
  pages =	{129--146},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-57-6},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{32},
  editor =	{Finlayson, Mark A. and Fisseni, Bernhard and L\"{o}we, Benedikt and Meister, Jan Christoph},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2013.129},
  URN =		{urn:nbn:de:0030-drops-41528},
  doi =		{10.4230/OASIcs.CMN.2013.129},
  annote =	{Keywords: narratives, similarity, common summary, empirical study, questionnaire}
}

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Documents authored by Michael, Loizos

Gathering Background Knowledge for Story Understanding through Crowdsourcing

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Narrative Similarity as Common Summary

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