The knowledge in slot and filler systems is structured as a set of entities and their attributes. Two views of this kind of structure are Semantic Nets and Frames.
In semantic net, information is represented as a set of nodes connected to each other by a set of labeled arcs, which represent relationship among the nodes. In earlier days, semantic nets were used to find relationships among the nodes by spreading out the activation from each node and seeing where they both met. This process is known as Intersection Search.
Many unary predicates can be easily converted into binary predicates. For example,
player(sachin) could be written as instance(player,sachin).
Three or more place predicates are easily convertible to binary predicates by creating new object for entire predicate statement.Some earlier uses of semantic nets were in English understanding program.
In semantic net, information is represented as a set of nodes connected to each other by a set of labeled arcs, which represent relationship among the nodes. In earlier days, semantic nets were used to find relationships among the nodes by spreading out the activation from each node and seeing where they both met. This process is known as Intersection Search.
Many unary predicates can be easily converted into binary predicates. For example,
player(sachin) could be written as instance(player,sachin).
Three or more place predicates are easily convertible to binary predicates by creating new object for entire predicate statement.Some earlier uses of semantic nets were in English understanding program.