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.
[1]
Thomas R. Gruber,et al.
A translation approach to portable ontology specifications
,
1993,
Knowl. Acquis..
[2]
Weishan Zhang,et al.
Product Line Based Ontology Development for Semantic Web Service
,
2006,
2006 Second IEEE International Symposium on Service-Oriented System Engineering (SOSE'06).
[3]
H. Duez-Rodriguez,et al.
Ontology-Based Knowledge Retrieval
,
2008,
2008 Seventh Mexican International Conference on Artificial Intelligence.
[4]
Adam Pease,et al.
Towards a standard upper ontology
,
2001,
FOIS.
[5]
Mark Needleman,et al.
The W3C Semantic Web Activity
,
2003
.