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Storytelling with Signal Injection: Focusing Stories with Domain Knowledge

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Machine Learning and Data Mining in Pattern Recognition (MLDM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10935))

Abstract

Given a beginning and ending document, automated storytelling attempts to fill in intermediary documents to form a coherent story. This is a common problem for analysts; they often have two snippets of information and want to find the other pieces that relate them. The goal of storytelling is to help the analysts limit the number of documents that must be sifted through and show connections between events, people, organizations, and places. But existing algorithms fail to allow for the insertion of analyst knowledge into the story generation process. Often times, analysts have an understanding of the situation or prior knowledge that could be used to focus the story in a better way. A storytelling algorithm is proposed as a multi-criteria optimization problem that allows for signal injection by the analyst while maintaining good story flow and content.

No one ever made a decision because of a number, they needed a story.

Daniel Kahneman,

Nobel Memorial Prize in Economics, 2002

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Acknowledgements

This work was supported by the In-house Laboratory Independent Research (ILIR) program, the Navy Innovative Science and Engineering (NISE) program, Missile Defense Agency (MDA) contract HQ0147-17-C-7605, and the Office of Net Technical Assessment (ONTA) within the Office of the Assistant Secretary of Defense for Research and Engineering (ASD R&E).

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Authors and Affiliations

  1. Naval Surface Warfare Center, 18372 Frontage Road, Dahlgren, VA, 22448, USA

    J. T. Rigsby

  2. CS Department, George Mason University, Mail Stop 4A5, Fairfax, VA, 22030, USA

    J. T. Rigsby & Daniel Barbará

Authors
  1. J. T. Rigsby
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  2. Daniel Barbará
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Corresponding author

Correspondence to J. T. Rigsby .

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Editors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, Leipzig, Germany

    Petra Perner

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Rigsby, J.T., Barbará, D. (2018). Storytelling with Signal Injection: Focusing Stories with Domain Knowledge. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2018. Lecture Notes in Computer Science(), vol 10935. Springer, Cham. https://doi.org/10.1007/978-3-319-96133-0_32

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  • DOI: https://doi.org/10.1007/978-3-319-96133-0_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96132-3

  • Online ISBN: 978-3-319-96133-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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