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Story creation from heterogeneous data sources

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Abstract

There are numerous applications where there is a need to rapidly infer a story about a given subject from a given set of potentially heterogeneous data sources. In this paper, we formally define a story to be a set of facts about a given subject that satisfies a “story length” constraint. An optimal story is a story that maximizes the value of an objective function measuring the goodness of a story. We present algorithms to extract stories from text and other data sources. We also develop an algorithm to compute an optimal story, as well as three heuristic algorithms to rapidly compute a suboptimal story. We run experiments to show that constructing stories can be efficiently performed and that the stories constructed by these heuristic algorithms are high quality stories. We have built a prototype STORY system based on our model—we briefly describe the prototype as well as one application in this paper.

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Authors and Affiliations

  1. Department of Computer Science, University of Maryland, A.V. Williams Building, College Park, MD, 20742, USA

    Marat Fayzullin & V. S. Subrahmanian

  2. Dipartimento di Informatica e Sistemistica, Università di Napoli “Federico II”, Via Claudio 21, 80125, Napoli, Italy

    Massimiliano Albanese, Carmine Cesarano & Antonio Picariello

Authors
  1. Marat Fayzullin
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  2. V. S. Subrahmanian
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  3. Massimiliano Albanese
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  4. Carmine Cesarano
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  5. Antonio Picariello
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Corresponding author

Correspondence to Antonio Picariello.

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Fayzullin, M., Subrahmanian, V.S., Albanese, M. et al. Story creation from heterogeneous data sources. Multimed Tools Appl 33, 351–377 (2007). https://doi.org/10.1007/s11042-007-0100-4

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  • DOI: https://doi.org/10.1007/s11042-007-0100-4

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