Knowledge Learning by Using Case Based Reasoning (CBR)

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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
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Whats 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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CBR System Components

• Case-base
• 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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The Case Based Reasoning Cycle
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Case Retrieval and Adaptation

• Case retrieval
• 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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Open Tools

• freeCBR
• is a free open source Java implementation of a
  "Case Based Reasoning" engine. (http//freecbr.sou
  rceforge.net/)
• myCBR
• is an open-source case-based reasoning tool
  developed at DFKI. (http//mycbr-project.net/index
  .html)

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freeCBR
a very small case set
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freeCBR (cont.)
search from the case set
the result of the search
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Open Tool myCBR
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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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Case Retrieval

• 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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Case Retrieval

• Decision Tree
• e.g.

Case-Base indexedusing a decision-tree
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Case Retrieval

• We propose a self-organizing reservoir
  computing based network for case retrieval.

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,
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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NARMA task
Mean squared error 0.128221, std 0.0200301
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• Future Work
• Integrate RC based network into CBR system
• Develop the CBR system based on existing tools
  for more complicated tasks