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Knowledge representation and retrieval

Prof. Joe Austerweil
University of Wisconsin - Madison ~ Psychology

In this talk, I focus on one facet of my research program: knowledge retrieval. I formulate, describe, and extend a novel model that retrieves items by randomly following associations between items in memory. I show how this model can capture patterns in how people retrieve items from a category, patterns that previously were used to argue that memory search must be guided by a strategic, rather than a random process. Further, I show that for a random search over knowledge to capture human memory retrieval, knowledge must be represented in a structured manner (e.g., network), and that a spatial representation is insufficient. Extending the new model, I develop and empirically validate a novel machine learning method for estimating network representations of groups and individuals efficiently. I then apply this method to reveal differences between the knowledge representations of older individuals that are cognitively impaired and matched controls. I will conclude with a discussion of an in progress project, which examines healthy and unhealthy cognitive aging using a low-cost, naturalistic microlongitudinal design.


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Cite this as:

Austerweil, J. L. (2021, July). Knowledge representation and retrieval. Paper presented at Virtual MathPsych/ICCM 2021. Via