Name
Abstract | ||
|---|---|---|
Cognitive modeling as a method has proven successful at reproducing and explaining human intelligent behavior in specific laboratory situations, but still struggles to produce more general intelligent capabilities. A promising strategy to address this weakness is the addition of large semantic resources to cognitive architectures. We are investigating the usefulness of this approach in the context of human behavior during software use. By adding world knowledge from a Wikipedia-based ontology to a model of human sequential behavior, we achieve quantitatively and qualitatively better fits to human data.The combination of model and ontology yields additional insights that cannot be explained by the model or the ontology alone. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-21365-1_27 | AGI |
Keywords | Field | DocType |
Cognitive modeling,Ontology,Human performance,Human error,Memory for goals | Ontology (information science),Ontology alignment,Ontology-based data integration,Ontology,Process ontology,Computer science,Human error,Artificial intelligence,Cognitive model,Cognition,Machine learning | Conference |
Volume | ISSN | Citations |
9205 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marc Halbrügge | 1 | 4 | 1.44 |
| Michael Quade | 2 | 2 | 0.72 |
| Klaus-Peter Engelbrecht | 3 | 98 | 10.88 |