TopBackground
Researchers in the field of information and knowledge systems have been working since early 1960s to provide a system which can represent, process, and retrieve knowledge in accordance to human information system which is brain. Graph based semantic representation have been the focus from the beginning (Sowa, 2008). Neuroscientists believe that the brain structure and function can be appropriately represented using network based approach (Sporns, 2011).
Knowledge representation has taken many forms ranging from cognitive maps (Kitchin,1994), concept maps, mind maps (Farrand, Hussain, & Hennessy, 2002), conceptual graphs and knowledge networks (Sowa, 1984; Chein & Mugnier, 2008).
Edward (1948) introduced the concept of cognitive maps, and Kosko (1993) introduced a fusion of fuzzy logic and cognitive map as Fuzzy Cognitive Maps (FCM). Cognitive maps provide mental representation of spatial information (Kitchin, 1994). Sowa (1976) developed a version of conceptual graphs (CG) as an intermediate language for mapping natural language questions and assertions to a relational database. CG provides a fixed diagram with labeled boxes and directed arrows (Figure 1).
Figure 1. CG display form for Jess travel to school by bicycle
Every semantic feature of the graph can be represented using a linear notation termed as Conceptual Graph Interchange Format (CGIF). CGIF is a concrete dialect that is capable of expressing the full Common Logic (CL) semantics. For the CG shown in Figure 1, the core CGIF is given as follows:
(∃x)(∃y)(Go(x) Person(Jess) Place(School) Bicycle(∧ ∧ ∧ y)(∧ x,Jess) Dest(∧ x, School) Inst(∧ x,y))