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filler structures.pptx
- 2. Inheritable knowledge • The relational knowledge base determines a set of attributes and associated values that together describe the objects of knowledge base. E.g. Player_info(“john”,”6.1”,180,right_throws) • The knowledge about the objects, their attributes and their values need not be as simple as shown. • One of the most powerful form of inference mechanisms is property inheritance. Player Height Weight Bats_throws John 6.1 180 Right_throws Sam 5.10 170 right_right Jack 6.2 215 Bats_throws
- 3. • Property Inheritance • Here elements of specific classes inherit attributes and values from more general classes in which they are included. • In order to support property inheritance objects must be organized into classes and classes must be arranged in generalization hierarchy.
- 4. and boxed nodes== object/values of attriibutesof an objjectt.. person(Owen) instance(Owen, Person) team(Owen, Liverpool) Here, Lines ==attributes This structure is also called as slot and filler structure. These structures are the devices to support property inheritance along isa and instance links. Mammal P P e e r r s s o o n n Owen Nose Red Liverpool isa instance h h a a s s - - p p a a r r t t uniform colour team
- 5. • Advantage of slot and filler structures: 1. monotonic reasoning can be performed more effectively than with pure logic and non monotonic reasoning is easily supported. 2. Makes it easy to describe properties of relations. e.g. “does Owen has-part called nose?” 3. Form of object oriented programming and has advantages such as modularity and ease of viewing by people.
- 6. Slot and filler structures Weak slot and filler structure Strong slot and filler structure Frames Semantic nets Scripts Conceptual Dependency Weak slot and filler structures: are “Knowledge- Poor” or “weak” as very little importance is given to the specific knowledge the structure should contain. Attribute= slot and its value= filler
- 7. Semantic nets • In semantic nets information is represented as: – set of nodes connected to each other by a set of labelled arcs. • Nodes represent: various objects / values of the attributes of object . • Arcs represent: relationships among nodes. Mammal Person Jack Nose Blue Chicago Royals isa instance has-part uniform color team
- 8. • In this network we could use inheritance to derive the additional info: has_part(jack, nose) Intersection Search One way to find relationships among objects is to spread the activation(links) out from two nodes and find out where it meets Ex: relation between : Red and liverpool Mammal Person Owen Nose Red Liverpool isa instance has-part uniform color team
- 9. • Representing non binary predicates: 1. Unary – e.x. Man(marcus) can be converted into: instance(marcus,Man) 2. Other arities- e.x. Score(india,australia,4-1) 3 or more place predicates can be converted to binary form as follows: 1. Create new object representing the entire predicate. 2. Introduce binary predicates to describe relation to this new object.
- 10. TEST4 isa Game Australia India 4-1 Visiting _team Score Home _team Score(india,australia,4-1)
- 11. Ex. 2. “john gave the book to Mary” give(john,mary,book) EV 1 instance Give John Mary Book BK1 instance Object agent beneficiary
- 12. Making some important distinctions 1. “john has height 72” 2. “john is taller than Bill” John 72 height John Bill H1 H2 height height Value 72 greater_than
- 13. Partitioned semantic nets • Used to represent quantified expressions in semantic nets. • One way to do this is to partition the semantic net into a hierarchical set of spaces each of which corresponds to the scope of one or more variable. • “the dog bit the mail carrier” [partitioning not required] d Dogs b Bite m Mail-Carrier isa isa isa assailant victim
- 14. • “every dog has bitten a mail carrier” x: dog (x) y: mail-carrier(y) bite(x, y) • How to represent universal quantifiers? – Let node ‘g’ stands for assertion given above – This node is an instance of a special class ‘GS’ of general statements about the world. – Every element in ‘GS’ has 2 attributes:- • Form - states relation that is being asserted. • connections - one or more, one for each of the universally quantified variables. – ‘SA’ is the space of partitioned sementic net.
- 15. • “every dog has bitten a mail carrier” SA S1 d Dogs b Bite m Mail-Carrier isa isa isa assailant victim g GS isa form
- 16. • “Every dog in the town has bitten the constable” SA m Constables isa S1 d Dogs b Bite isa isa assailant g GS isa form victim
- 17. • “Every dog in the town has bitten every constable” SA Constables S1 d Dogs b Bite isa isa assailant g GS isa form victim c isa
- 18. • More examples of sementic nets: • “ Mary gave the green flowered vase to her favourite cousin” EV 1 instance Give Mary cousin vase Object agent beneficiary Colour_pattern Green flowered favourite
- 19. • “every batsman hits a ball” SA S1 b Batsman Hits b Balls isa isa isa action Acts_on g GS isa form h
- 20. • “Tweety is a kind of bird who can fly. It is Yellow in colour and has wings.” Bird Tweety Wings instance has-part yellow fly colour action
- 21. • Represent following using sementic nets:- Tom is a cat. Tom caught a bird. Tom is owned by John. Tom is ginger in color. Cats like cream.The cat sat on the mat. Acat is a mammal. Abird is an animal. All mammals are animals.mammals have fur.
- 22. Frames • Another kind of week slot and filler structure. • Frame is a collection of attributes called as slots and associated values that describe some entity in the world (filler). • Consider, Room Hotel room isa Hotel bed contains Hotel Chair contains Location Chair Sitting_on 4 20-40 cms isa use legs height Room No 2 instance
- 23. Hotel Room isa : Room contains: Hotel Bed contains: Hotel Chair Hotel Chair isa: Chair use: sitting_on location: Hotel Room . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Frame System for Hotel Room Frame structure for Hotel Room Frame structure for Hotel Chair Frame structure for all remaining attributes
- 24. Person Jack_Roberts instance: Fielder height: 5-10 balls: right batting_avg: 0.309 team: Chicagocubs uniform_color: blue Fielder isa: ML_Baseball_Player cardinality: 376 batting_avg: 0.262 ML_Baseball_Team isa:T eam cardinality: 26 team_size: 24 manager: isa: Mammal cardinality: 6,000,000,000 * Handed: right Adult Male isa: Person Cardinality: 2,000,000,000 * Height: 5- 10 ML_Baseball_Player isa:Adult_Male cardinality: 624 * height: 6-1 * bats: equal tohanded * batting-avg: 0.252 * team: *uniform_color: Individual frame
- 25. • Meta Class: special class whose elements themselves are classes. – If X is meta class and Y is another class which is an element of X, then Y inherits all the attributes of X. • Other ways of relating classes to each other 1. Mutually disjoint: 2 classes are mutually disjoint if they are guaranteed to have no elements in common. 2. Is covered by: relationship is called as ‘covered-by’ when we have a class and it has set of subclasses, the union of which is equal to the superclass. ML_Baseball_Player isa Fielder Pitcher isa Catcher isa American Leaguer isa National Leaguer isa Jack instance instance
- 26. ML_Baseball_Player is covered-by: { Pitcher, Catcher, Fielder,American leaguer, National leaguer} Pitcher isa: ML_Baseball_Player mutually_disjoint-with: {Catcher, Fielder } Catcher isa: ML_Baseball_Player mutually_disjoint-with: {Pitcher, Fielder } Fielder isa: ML_Baseball_Player mutually_disjoint-with: {Pitcher, Catcher} . . . .
- 27. Tangled Hierarchies • Hierarchies that are not trees • Usually hierarchy is an arbitrary directed acyclic graph. • Tangled hierarchies requires new property inheritance algorithm.
- 28. • FIGURE A • Can fifi fly? • The correct answer must be ‘no’. – Although birds in general can fly, the subset of birds , ostriches does not. – Although class pet bird provides path from fifi to bird and thus to the answer that fifi can fly, it provides no info that conflicts with the special case knowledge associated with class ostrich, so it should hove no effect on the answer. isa isa isa isa Ostrich fly :no fifi fly : ? Bird fly :yes Pet-Bird