Title :
Semantic nets as paradigms for both causal and judgemental knowledge representation
Author :
Burns, James R. ; Winstead, Wayland H. ; Haworth, Dwight A.
Author_Institution :
Coll. of Bus. Adm., Texas Tech. Univ., Lubbock, TX, USA
Abstract :
The use of semantic nets to represent causation in static and dynamic processes is proposed. Their conventional usage as mechanisms for representing judgemental and experimental knowledge is reviewed. A specific semantic net called an M-labeled digraph is investigated with respect to its potential for evolving a more unified and holistic knowledge representation paradigm. A breadth-first inference engine utilizing Boolean multiplication of binary matrices is presented. Limitations of the method are discussed
Keywords :
Boolean algebra; directed graphs; grammars; inference mechanisms; knowledge representation; Boolean multiplication; M-labeled digraph; binary matrices; breadth-first inference engine; causation; dynamic processes; experimental knowledge; judgemental knowledge; judgemental knowledge representation; semantic nets; static processes; Engines; Humans; Inference algorithms; Knowledge representation; Labeling; Logic; Operations research; Sociotechnical systems;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
