the role of prior knowledge in human reconstructive memory mark steyvers pernille hemmer university...
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The Role of Prior Knowledge in Human Reconstructive Memory
Mark Steyvers
Pernille Hemmer
University of California, Irvine
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Interaction between Prior Knowledge & Episodic Memory
2
Episodic MemoryPrior Knowledge,
Semantic Memory,“Schemas”
“What objects do you remember from your hotel room?”“What coffee did you order from Starbucks last week?”
reconstructive memory
Research questions
Machine learning How can we formalize prior knowledge (“schemas”)?
Psychology How do humans integrate memory and prior knowledge? What errors do people make?
Interface between human & machine learning Can we explain human error with rational inference principles? Can we build better information retrieval systems by taking
cognitive processes into account?
3
Remembering Objects from a Graduate Office
Brewer & Treyens (1981)
chairdeskskull
books
(30% of subjects)
Experiments
perception: list objects you see in a scene memory: list objects you remember from a scene guessing: list objects you might see in a kitchen/office/…
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Dining Hotel Kitchen
Human Data: Precision vs. Output Position
6
2 4 6 8 10 12 14 160.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Output Position
Cu
mu
lativ
e A
ccur
acy
Time = 10secsTime = 2secsScene Cue
guessing
10 Secs.
2 Secs
Pre
cisi
on
Bayesian Analysis of Reconstructive Memory
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( | ) ( | ) ( )p objects memory p memory objects p objects
Posterior
What objects were studied given noisy memory contents?
Prior
How likely are these objects a
priori?
Likelihood
How likely is this memory content
given these objects were studied?
Problem 1: Infer prior knowledge
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kitchen1 kitchen3kitchen2
PriorKnowledge ?
Hierarchical Beta processes (Thibaux & Jordan, 2007); related to Indian Buffet process
Hierarchical Beta Process(Thibaux & Jordan, 2007)
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“Kitchen”
Kitchen65
objects
pa
rtic
ipa
nts
Kitchen45
0 0 0 0~ Beta( , (1 ))b c b c b
Generalknowledge
Object probs. for specific
image
Reported objects
y
ja
b
~ Beta( , (1 ))j j ja c b c b
~ Bernoulli( )ij jy a
Problem 2: Recall using Prior + Episodic M.
10
?
PriorKnowledge b
Actual objects in image
Noisy Memory Content
y
x
semantic memory
episodic memory
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Data Model
2 4 6 8 10 12 14 160.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Output Position
Cu
mu
lativ
e A
ccur
acy
=0.200=0.150=0.000
2 4 6 8 10 12 14 160.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Output Position
Cumu
lative
Acc
uracy
Time = 10secsTime = 2secsScene Cue10 Secs.
2 Secs
Pre
cisi
on
prior only
Limitations of Model
Independence assumption between objects
Recall often clusters correlated objects “computer” “mouse” “keyboard”
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Reconstructing the Style of Written Digits
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Study
Reconstructed
studied digit
reconstructed
personalprior
Digit space from “Earth Mover” distances
Reconstructing Drawings from Memory
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Studied Drawing Reconstruction
Reconstructing Lists of Words
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Study this list:PEAS, CARROTS, BEANS, SPINACH, LETTUCE, HAMMER, TOMATOES, CORN, CABBAGE, SQUASH
HAMMER,PEAS,
CARROTS,...
Conclusion
Prior knowledge has strong effect on memory Guessing based on prior knowledge leads to quite good
performance
Machine learning methods help formalize “schemas”
Useful to understand human memory when designing information retrieval systems
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Thanks!
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