1. Knowledge Learning by Using Case Based Reasoning (CBR)
Jun Yin and Yan Meng
Department of Electrical and Computer Engineering
Stevens Institute of Technology
Hoboken, NJ, USA
4/24/2017

2. What’s CBR?
Case-Based Reasoning (CBR) is a name given to a reasoning method that solves a new problem by remembering a previous similar experiences and by reusing information and knowledge of that situation.
Ex: Medicine
doctor remembers previous patients especially for rare combinations of symptoms
Ex: Law
English/US law depends on precedence
case histories are consulted
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3. CBR System Components Case-base Retrieval of relevant cases
database of previous cases (experience)
Retrieval of relevant cases
matching most similar case(s)
retrieving the solution(s) from these case(s)
Adaptation of solution
alter the retrieved solution(s) to reflect differences between new case and retrieved case(s)
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4. The Case Based Reasoning Cycle
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The Case Based Reasoning Cycle

5. Case Retrieval and Adaptation
the process of finding within the case base those cases that are the closest to the current case.
Nearest Neighbor Retrieval
Inductive approaches
Knowledge Guided Approaches
Validated Retrieval
Case Adaptation
the process of translating the retrieved solution into the solution appropriate for the current problem.
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6. Open Tools
freeCBR
is a free open source Java implementation of a "Case Based Reasoning" engine. (
myCBR
is an open-source case-based reasoning tool developed at DFKI. (
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7. freeCBR
a very small case set:
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8. freeCBR (cont.) search from the case set: the result of the search:
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9. Open Tool – myCBR
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10. Open Tools – freeCBR & myCBR
Modeling Similarity Measures:
These two tools follow the approach in which, for an attribute-value based case representation consisting of n attributes, the similarity between a query q and a case c may be calculated as follows:
Here, simi and wi denote the local similarity measure and the weight of attribute i, and Sim represents the global similarity measure.
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11. Case Retrieval Retrieve most similar k-nearest neighbor - k-NN
Nearest Neighbor Retrieval
Retrieve most similar
k-nearest neighbor
- k-NN
- like scoring in bowls or curling
Example
1-NN
5-NN
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12. Case Retrieval Case-Base indexed using a decision-tree Decision Tree
e.g.
Case-Base indexed using a decision-tree
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13. Case Retrieval
We propose a self-organizing reservoir computing based network for case retrieval.
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14. ,
Case Retrieval
Benchmark to evaluate the performance of proposed RC based network.
NARMA task
- The Nonlinear Auto-Regressive Moving Average (NARMA) task consists of modeling the output of the following tenth-order system :
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15. NARMA task:
Mean squared error = , std =
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16. Future Work
Integrate RC based network into CBR system
Develop the CBR system based on existing tools for more complicated tasks
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