Diagnosing Alternative Facts

10 pages•Published: January 6, 2018

Johan de Kleer, Matthew Klenk and Alexander Feldman

Abstract

This paper presents an approach to applying model-based diagnosis to the task of interpreting in- formation from a wide variety of sources: text, video, meta-data, audio, etc. Much of the information contained in the sources is contradictory, incomplete, purposely deceptive or biased. People make critical decisions based on such murky information. By automating the construction of alternatives, we can design systems that support intelligence analysts and ordinary citizens in understanding the world. We have developed a preliminary version of our HCDX tool (hypothesis construction through diagnosis). We plan to distribute this tool as open source.

Keyphrases: disambiguating knowledge, knowledge representation, model based diagnosis

In: Marina Zanella, Ingo Pill and Alessandro Cimatti (editors). 28th International Workshop on Principles of Diagnosis (DX'17), vol 4, pages 159-168.

Links:	https://easychair.org/publications/paper/rnKw
	https://doi.org/10.29007/fkwg

BibTeX entry

@inproceedings{DX'17:Diagnosing_Alternative_Facts,
  author    = {Johan de Kleer and Matthew Klenk and Alexander Feldman},
  title     = {Diagnosing Alternative Facts},
  booktitle = {28th International Workshop on Principles of Diagnosis (DX'17)},
  editor    = {Marina Zanella and Ingo Pill and Alessandro Cimatti},
  series    = {Kalpa Publications in Computing},
  volume    = {4},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/rnKw},
  doi       = {10.29007/fkwg},
  pages     = {159-168},
  year      = {2018}}

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