Attribute Exploration with Multiple Contradicting Partial Experts

TL;DR

This paper extends attribute exploration in Formal Concept Analysis to accommodate multiple experts with potentially conflicting views, enabling collaborative knowledge discovery in complex domains.

Contribution

It introduces a novel method for attribute exploration that integrates multiple experts' perspectives, including contradictions, to identify shared domain structures.

Findings

Supports multiple expert inputs with contradictions

Enables discovery of shared attribute dependencies

Improves collaborative knowledge exploration

Abstract

Attribute exploration is a method from Formal Concept Analysis (FCA) that helps a domain expert discover structural dependencies in knowledge domains which can be represented as formal contexts (cross tables of objects and attributes). In this paper we present an extension of attribute exploration that allows for a group of domain experts and explores their shared views. Each expert has their own view of the domain and the views of multiple experts may contain contradicting information.