ConExp Tutorial @ HHAI 2024:

June 10, 2024, 14.00--18.00, NI:A0406

Tutorial at the third International Conference on Hybrid Human-Artificial Intelligence

There are various approaches towards synergetic human-AI cooperation with different objectives and frameworks. A particularly interesting purpose in science and beyond is the (structured) exploration of domain knowledge. In order to unravel its relational properties and the governing rules, various methods have been proposed in the literature.

In this tutorial we give an introduction to a very successful example of such a method: Conceptual Exploration. This is an AI-orchestrated knowledge acquisition process that can be performed by a human, an AI, or a combination of both. It enables a group of humans and AI to i) discover so far unknown knowledge, ii) identify common knowledge among the members of the group, and iii) pinpoint to contradictory knowledge.

Among other things, we will present the necessary mathematical foundations, discuss the algorithmic properties and complexities and show various examples of successful applications. As a special highlight, we will try to implement the method together with the participants and the knowledge graph Wikidata during the tutorial.

Organizers

Tutorial Material

Tutorial Slides

Literature and

  • Formal Concept Analysis: Mathematical Foundations DOI
  • Conceptual Exploration DOI

Software and more resources

  • Conexp-clj — a clojure (java) library (and some GUI) for FCA
  • fcaR — a package for doing FCA in R
  • concepts — a Python package for computing concepts
  • Overview — FCA – overview website by Uta Priss