2 citations · 6 across the 18 of their papers we have counts for
4 papers · 1 filter
Flexible categorization using formal concept analysis and Dempster-Shafer theory
Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano +3
The framework developed in the present paper provides a formal ground to generate and study explainable categorizations of sets of entities, based on the epistemic attitudes of ind…
Outlier detection using flexible categorisation and interrogative agendas
Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano +3
Categorization is one of the basic tasks in machine learning and data analysis. Building on formal concept analysis (FCA), the starting point of the present work is that different…
A Meta-Learning Algorithm for Interrogative Agendas
Erman Acar, Andrea De Domenico, Krishna Manoorkar +1
Explainability is a key challenge and a major research theme in AI research for developing intelligent systems that are capable of working with humans more effectively. An obvious…
Flexible categorization for auditing using formal concept analysis and Dempster-Shafer theory
Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano +3
Categorization of business processes is an important part of auditing. Large amounts of transnational data in auditing can be represented as transactions between financial accounts…