Attribute Exploration with Multiple Contradicting Partial Experts

05/31/2022
by   Maximilian Felde, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/04/2021

Triadic Exploration and Exploration with Multiple Experts

Formal Concept Analysis (FCA) provides a method called attribute explora...
research
08/23/2019

Interactive Collaborative Exploration using Incomplete Contexts

A common representation of information about relations of objects and at...
research
02/05/2019

An Exploratory Study on Visual Exploration of Model Simulations by Multiple Types of Experts

Experts in different domains rely increasingly on simulation models of c...
research
09/07/2022

ErgoExplorer: Interactive Ergonomic Risk Assessment from Video Collections

Ergonomic risk assessment is now, due to an increased awareness, carried...
research
12/23/2017

Towards Collaborative Conceptual Exploration

In domains with high knowledge distribution a natural objective is to cr...
research
02/17/2017

Towards a Unified Taxonomy of Biclustering Methods

Being an unsupervised machine learning and data mining technique, biclus...
research
03/29/2023

Three-way causal attribute partial order structure analysis

As an emerging concept cognitive learning model, partial order formal st...

Please sign up or login with your details

Forgot password? Click here to reset