Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation
Galea, David & Bruza, Peter (2016) Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation. In Atmanspacher, Harald, Filk, Thomas, & Pothos, Emmanuel (Eds.) Quantum Interaction: 9th International Conference, QI 2015, Revised Selected Papers, Springer International Publishing, Filzbach, Switzerland, pp. 258-271.
This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data.
In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed  with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models.
Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors . Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus.
It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.
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|Item Type:||Conference Paper|
|Keywords:||quantum theory, human memory|
|Subjects:||Australian and New Zealand Standard Research Classification > PSYCHOLOGY AND COGNITIVE SCIENCES (170000) > COGNITIVE SCIENCE (170200) > Computer Perception Memory and Attention (170201)
Australian and New Zealand Standard Research Classification > LANGUAGES COMMUNICATION AND CULTURE (200000) > LINGUISTICS (200400) > Computational Linguistics (200402)
|Divisions:||Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2016 Springer International Publishing Switzerland|
|Copyright Statement:||The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-28675-4_20|
|Deposited On:||09 May 2016 23:12|
|Last Modified:||11 May 2016 00:05|
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