4 citations · 7 across the 3 of their papers we have counts for
4 papers
Graph Queries from Natural Language using Constrained Language Models and Visual Editing
Benedikt Kantz, Kevin Innerebner, Peter Waldert +3
Querying knowledge bases using ontologies is usually performed using dedicated query languages, question-answering systems, or visual query editors for Knowledge Graphs. We propose…
Differentiable Fuzzy Neural Networks for Recommender Systems
Stephan Bartl, Kevin Innerebner, Elisabeth Lex
As recommender systems become increasingly complex, transparency is essential to increase user trust, accountability, and regulatory compliance. Neuro-symbolic approaches that inte…
Hybrid Personalization Using Declarative and Procedural Memory Modules of the Cognitive Architecture ACT-R
Kevin Innerebner, Dominik Kowald, Markus Schedl +1
Recommender systems often rely on sub-symbolic machine learning approaches that operate as opaque black boxes. These approaches typically fail to account for the cognitive processe…
OnSET: Ontology and Semantic Exploration Toolkit
Benedikt Kantz, Kevin Innerebner, Peter Waldert +3
Retrieval over knowledge graphs is usually performed using dedicated, complex query languages like SPARQL. We propose a novel system, Ontology and Semantic Exploration Toolkit (OnS…