Information Fusion-2-Text: Explainable Aggregation via Linguistic Protoforms

Bryce J. Murray, Derek T. Anderson, Timothy C. Havens, Tim Wilkin, Anna Wilbik

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Recent advancements and applications in artificial intelligence (AI) and machine learning (ML) have highlighted the need for explainable, interpretable, and actionable AI-ML. Most work is focused on explaining deep artificial neural networks, e.g., visual and image captioning. In recent work, we established a set of indices and processes for explainable AI (XAI) relative to information fusion. While informative, the result is information overload and domain expertise is required to understand the results. Herein, we explore the extraction of a reduced set of higher-level linguistic summaries to inform and improve communication with non-fusion experts. Our contribution is a proposed structure of a fusion summary and method to extract this information from a given set of indices. In order to demonstrate the usefulness of the proposed methodology, we provide a case study for using the fuzzy integral to combine a heterogeneous set of deep learners in remote sensing for object detection and land cover classification. This case study shows the potential of our approach to inform users about important trends and anomalies in the models, data and fusion results. This information is critical with respect to transparency, trustworthiness, and identifying limitations of fusion techniques, which may motivate future research and innovation.

Original languageEnglish
Title of host publicationInformation Processing and Management of Uncertainty in Knowledge-Based Systems - 18th International Conference, IPMU 2020, Proceedings
EditorsMarie-Jeanne Lesot, Susana Vieira, Marek Z. Reformat, João Paulo Carvalho, Anna Wilbik, Bernadette Bouchon-Meunier, Ronald R. Yager
PublisherSpringer
Pages114-127
Number of pages14
ISBN (Print)9783030501525
DOIs
Publication statusPublished - 2020
Event18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020 - Lisbon, Portugal
Duration: 15 Jun 202019 Jun 2020

Publication series

NameCommunications in Computer and Information Science
Volume1239 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020
CountryPortugal
CityLisbon
Period15/06/2019/06/20

Keywords

  • Deep learning
  • Explainable artificial intelligence
  • Fuzzy integral
  • Information aggregation
  • Information fusion
  • Linguistic summary
  • Machine learning
  • Protoform
  • XAI

Fingerprint Dive into the research topics of 'Information Fusion-2-Text: Explainable Aggregation via Linguistic Protoforms'. Together they form a unique fingerprint.

  • Cite this

    Murray, B. J., Anderson, D. T., Havens, T. C., Wilkin, T., & Wilbik, A. (2020). Information Fusion-2-Text: Explainable Aggregation via Linguistic Protoforms. In M-J. Lesot, S. Vieira, M. Z. Reformat, J. P. Carvalho, A. Wilbik, B. Bouchon-Meunier, & R. R. Yager (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems - 18th International Conference, IPMU 2020, Proceedings (pp. 114-127). (Communications in Computer and Information Science; Vol. 1239 CCIS). Springer. https://doi.org/10.1007/978-3-030-50153-2_9