Distributed Case Based Reasoning Model with Semantic Intelligence
Keywords:
Case agency, case broker, case model, distributed decision, semantic intelligence.Abstract
The objective of the work is to propose a case
based reasoning (CBR) model with semantic intelligence for
deciding a fine tuned solution from a number of distributed
cases. A case model has been proposed to incorporate the
needed data types and certificates through which the local or
global authorities can reason out the solution. The n-tier model
of reasoning can be performed using a case agency and broker
components to file and adjudicate the results for the submitted
cases. The machine learning is emphasized through iterative
learning process with pre and post filters to fine tune the
solution based on the context of the case. The semantic
engineering is carried out to categorize the nature of the case in
terms of basic informal constructs. An inherent hierarchy of the
context is formed and based on the type and importance of the
context, the scenario driven solution is identified by this
proposed model. An airway passenger guidance system is
considered to validate the model of case based reasoning with
the help of decision tree technique.
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