  Research in the field of Artificial Intelligence is continually progressing
to simulate the human knowledge into automated intelligent knowledge base,
which can encode and retrieve knowledge efficiently along with the capability
of being is consistent and scalable at all times. However, there is no system
at hand that can match the diversified abilities of human knowledge base. In
this position paper, we put forward a theoretical model of a different system
that intends to integrate pieces of knowledge, Informledge System (ILS). ILS
would encode the knowledge, by virtue of knowledge units linked across
diversified domains. The proposed ILS comprises of autonomous knowledge units
termed as Knowledge Network Node (KNN), which would help in efficient
cross-linking of knowledge units to encode fresh knowledge. These links are
reasoned and inferred by the Parser and Link Manager, which are part of KNN.

Information Retrieval;Artificial Intelligence;Neural and Evolutionary Computing