Automated Generation of Cognitive Ontology via Web Text-Mining


A key goal of cognitive science is to understand and map the relationship between cognitive processes. Previous works have manually curated cognitive terms and relations, effectively creating an ontology, but do they reflect how cognitive scientists study cognition in practice? In addition, cognitive science should provide theories that inform experimentalists in neuroscience studying implementations of cognition in the brain. But do neuroscientists and cognitive scientists study the same things? We set out to answer these questions in a data-driven way by text-mining and automated clustering to build a cognitive ontology from existing literature. We find automatically generated relationships to be missing in existing ontologies, and that cognitive science does not always inform neuroscience. Thus, our work serves as an efficient hypothesis-generating mechanism, inferring relationships between cognitive processes that can be manually refined by experts. Furthermore, our results highlight the gap between theories of cognition and the study of their implementation.

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