Book Chapter has been published

We are happy to announce that our book chapter “Semantic Web Machine Learning Systems: An Analysis of System Patterns” has been published as part of the “Compendium of Neurosymbolic Artificial Intelligence” book.

The book is a collection of 30 chapters and around 700 pages, covering multiple aspects of neurosymbolic AI.

Our chapter is based on our article “Combining Machine Learning and Semantic Web: A Systematic Mapping Study” also published this year, read about it on our blog.

The book chapter further details the range of system patterns discovered in the original study. These patterns consist of two main building blocks (data and processing blocks) and represent the architectural makeup of systems combining both symbolic and subsymbolic approaches.

Concrete examples of each pattern type (Atomic, Fusion, I-, Y-, T- and complex patterns) are provided and discussed in more detail. Examples for simple patterns (Atomic and Fusion) are provided in Figure 1.

We are looking forward to your feedback and questions!