62 citations · 144 across the 11 of their papers we have counts for
12 papers
SUBMASSIVE: Resolving Subclass Cycles in Very Large Knowledge Graphs
Shuai Wang, Peter Bloem, Joe Raad +1
Large knowledge graphs capture information of a large number of entities and their relations. Among the many relations they capture, class subsumption assertions are usually presen…
Towards Semantically Enriched Embeddings for Knowledge Graph Completion
Mehwish Alam, Frank van Harmelen, Maribel Acosta
Embedding based Knowledge Graph (KG) Completion has gained much attention over the past few years. Most of the current algorithms consider a KG as a multidirectional labeled graph…
Refining neural network predictions using background knowledge
Alessandro Daniele, Emile van Krieken, Luciano Serafini +1
Recent work has shown logical background knowledge can be used in learning systems to compensate for a lack of labeled training data. Many methods work by creating a loss function…
Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases
Michael van Bekkum, Maaike de Boer, Frank van Harmelen +2
The unification of statistical (data-driven) and symbolic (knowledge-driven) methods is widely recognised as one of the key challenges of modern AI. Recent years have seen large nu…
Analyzing Differentiable Fuzzy Implications
Emile van Krieken, Erman Acar, Frank van Harmelen
Combining symbolic and neural approaches has gained considerable attention in the AI community, as it is often argued that the strengths and weaknesses of these approaches are comp…
Analyzing Differentiable Fuzzy Logic Operators
Emile van Krieken, Erman Acar, Frank van Harmelen
The AI community is increasingly putting its attention towards combining symbolic and neural approaches, as it is often argued that the strengths and weaknesses of these approaches…
Semi-Supervised Learning using Differentiable Reasoning
Emile van Krieken, Erman Acar, Frank van Harmelen
We introduce Differentiable Reasoning (DR), a novel semi-supervised learning technique which uses relational background knowledge to benefit from unlabeled data. We apply it to the…
Reinforcement Learning for Personalized Dialogue Management
Floris den Hengst, Mark Hoogendoorn, Frank van Harmelen +1
Language systems have been of great interest to the research community and have recently reached the mass market through various assistant platforms on the web. Reinforcement Learn…
The sameAs Problem: A Survey on Identity Management in the Web of Data
Joe Raad, Nathalie Pernelle, Fatiha Saïs +2
In a decentralised knowledge representation system such as the Web of Data, it is common and indeed desirable for different knowledge graphs to overlap. Whenever multiple names are…
Observing LOD using Equivalent Set Graphs: it is mostly flat and sparsely linked
Luigi Asprino, Wouter Beek, Paolo Ciancarini +2
This paper presents an empirical study aiming at understanding the modeling style and the overall semantic structure of Linked Open Data. We observe how classes, properties and ind…
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems
Frank van Harmelen, Annette ten Teije
We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from kno…
Theoretical And Technological Building Blocks For An Innovation Accelerator
Frank van Harmelen, George Kampis, Katy Borner +10
The scientific system that we use today was devised centuries ago and is inadequate for our current ICT-based society: the peer review system encourages conservatism, journal publi…