Semantic networks Knowledge Representation

Semantic networks Knowledge Representation. Network Operation • To infer new information from semantic networks, we can ask questions from nodes. • Ask node vehicle: ‘How do you travel?’ – This node looks at arc and replies: road - Asks node Car (because of IS-A relationship) – Asks node Vehicle (IS-A relationship) – Node Vehicle Replies: road Semantic networks(Cont..) Problems with Semantic Networks • Semantic networks are computationally expensive at run-time as we need to traverse the network to answer some question. In the worst case, we may need to traverse the entire network and then discover that the requested info does not exist. • They try to model human associative memory (store information using associations), but in the human brain the number of neurons and links are in the order of 1015. It is not practical to build such a large semantic network, hence this scheme is not feasible for this type of problems. Semantic networks(Cont..) Problems with Semantic Networks(cont) • Semantic networks are logically inadequate as they do not have any equivalent quantifiers, e.g., for all, for some, none. Frames • “Frames are data structures for representing stereotypical knowledge of some concept or object” according to Durkin, a frame is like a schema, as we would call it in a database design. They were developed from semantic networks and later evolved into our modern-day Classes and Objects. For example, to represent a student, we make use of the following frame: