201. Controlling the retrieval of general vs specific semantic knowledge in the instancetheory of semantic memory
- Author
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Crump, Matthew J.C., Jamieson, Randall K., Johns, Brendan T., and Jones, Michael N.
- Subjects
distributional semantics ,higher-order similarity ,instance theory ,surprise-driven learning ,retrieval - Abstract
Distributional models of semantic cognition commonly makesimplifying assumptions, such as representing word co-occurrence structure by prototype-like high-dimensional se-mantic vectors, and limit how retrieval processes may con-tribute to the construction and use of semantic knowl-edge. More recently, the instance theory of semantics (ITS,Jamieson, Avery, Johns, & Jones, 2018) reconceived a dis-tributional model in terms of instance-based memory, allow-ing context-specific construction of semantic knowledge at thetime of retrieval. By simulation, we show that additional en-coding and retrieval operations, consistent with learning andmemory theory, can play a crucial role in flexibly controllingthe construction of general versus specific semantic knowl-edge. We argue this consolidation of processing principlesholds insight for distributional theories of semantic cognition.
- Published
- 2020