Belief Revision and Formal Argumentation are two subfields of Knowledge Representation and Reasoning (KR) that deal with resolving inconsistencies in logic- based representations of information through dynamic processes.
One of the main goals of the artificial intelligence community is to create machines able to reason with dynamically changing knowledge.
Das Institut WEST betreibt die Netzwerkdatenbank KONECT. Die Datenbank hat die Funktion möglichst viele verschiedene Netzwerke zu katalogisieren. Ein Hinzufügen von Duplikaten stellt dabei ein Problem dar, da es Experimente, die auf dieser Datenbank ausgeführt werden, stark verfälscht.
Tracking ones heart rate (especially RR-Intervals) can be very effective for a persons health. Via the Baevsky stress index with the help of simple statistics one can determine if a person is stressed or chilled.
Evolutionary Linguistics is the study of the origins and the development of human language. Although most human languages differ substantially in the details they share a lot of general structure.
Semantic Web technologies facilitate Web data integration in an unprecedented manner. First, they are able to create a global knowledge base out of Web data sets which may have been defined in heterogeneous contexts and published in distributed locations.
Formal Concept Analysis (FCA) is a method that allows to identify concepts and their interrelationships in a well understood and formally sound way. Based on that, so called Iceberg Concept Lattices, introduced in the early 2000s, represent conceptual knowledge that is best supported in the data given a certain minimum support threshold.
The way in which companies benefit from open source software (OSS) communities varies and corresponds with the business strategy they maintain. One way of establishing influence in OSS communities is by deploying own resources to an OSS project.
Ontology debugging helps ontology engineers to find modelling errors in ontology. Most debugging methods relies on finding Minimal Unsatisfiability Preserving Sets (MUPS) inside an ontology.
Profiling applications are omnipresent in today's online life: product recommendations in online shops, personalised search platforms etc. Often, however, profiling systems fail to model the complexity of user interests and preferences in all their depth.