Combination of graphics, uncertainty, and semantics: A survey

Yuan Gao, Muhammad Adnan Rafi

Research output: Contribution to journalArticlepeer-review

Abstract

Graphics, uncertainty, and semantics are three approaches to building models. The combination of the three approaches is a way to develop a stronger modeling method. This article surveys the research efforts toward combining these aspects, which can be divided into two routes: One is to combine graphics and uncertainty as probabilistic graphical models and then incorporate semantics, and the other is to combine graphics and semantics and then incorporate probability to handle uncertainty. The models and methods involved in these efforts are introduced and their expressiveness, pros, and cons are discussed.
Original languageEnglish
JournalConcurrency and Computation
Early online date14 Nov 2021
DOIs
Publication statusE-pub ahead of print - 14 Nov 2021

Keywords

  • computer science
  • graph-based knowledge representation
  • knowledge representation
  • probabilistic graphical model
  • probability

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