  In an e-Learning system a learner may come across multiple unknown terms,
which are generally hyperlinked, while reading a text definition or theory on
any topic. It becomes even harder when one tries to understand those unknown
terms through further such links and they again find some new terms that have
new links. As a consequence they get confused where to initiate from and what
are the prerequisites. So it is very obvious for the learner to make a choice
of what should be learnt before what. In this paper we have taken the data
mining based frequent pattern graph model to define the association and
sequencing between the words and then adopted the Ant Colony Optimization, an
artificial intelligence approach, to derive a searching technique to obtain an
efficient and optimized learning path to reach to a unknown term.

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