AI_ 8 Weak Slot and Filler Structure

Frame Representation and Semantic Representation

1. Artificial Intelligence
Chap.8 Weak Slot and Filler
Structure
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Prof. KhushaliB Kathiriya

2. Outline
Semantic Net
Frame Representation
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3. Artificial Intelligence
Semantic net representation
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Prof. KhushaliB Kathiriya

4. 2. Semantic net representation
Semanticnetworksarealternativeofpredicatelogicforknowledge
representation.InSemanticnetworks,wecanrepresentourknowledgein
theformofgraphicalnetworks.Thisnetworkconsistsofnodesrepresenting
objectsandarcswhichdescribetherelationshipbetweenthoseobjects.
Semanticnetworkscancategorizetheobjectindifferentformsandcan
alsolinkthoseobjects.Semanticnetworksareeasytounderstandandcan
beeasilyextended.
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5. 2. Semantic net representation (Cont.)
Following are some statements which we need to represent in the form of
nodes and arcs.
1.Jerry is a cat.
2.Jerry is a mammal
3.Jerry is owned by Priya.
4.Jerry is brown colored.
5.All Mammals are animal.
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6. 2. Semantic net representation (Cont.)
Drawbacks in Semantic representation:
1.Semanticnetworkstakemorecomputationaltimeatruntimeasweneedto
traversethecompletenetworktreetoanswersomequestions.Itmightbe
possibleintheworstcasescenariothataftertraversingtheentiretree,we
findthatthesolutiondoesnotexistinthisnetwork.
2.Semanticnetworkstrytomodelhuman-likememory(Whichhas1015
neuronsandlinks)tostoretheinformation,butinpractice,itisnotpossible
tobuildsuchavastsemanticnetwork.
3.Thesetypesofrepresentationsareinadequateastheydonothaveany
equivalentquantifier,e.g.,forall,forsome,none,etc.
4.Semanticnetworksdonothaveanystandarddefinitionforthelinknames.
5.Thesenetworksarenotintelligentanddependonthecreatorofthesystem.
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7. 2. Semantic net representation (Cont.)
Advantages of Semantic network:
1.Semanticnetworksareanaturalrepresentationofknowledge.
2.Semanticnetworksconveymeaninginatransparentmanner.
3.Thesenetworksaresimpleandeasilyunderstandable.
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8. 2. Semantic net representation (Cont.)
Represent following sentences using semantic networks.
Isa(person, mammal)
Instance(Mike-Hall, person)
Team(Mike-Hall, Cardiff)
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9. 2. Semantic net representation (Cont.)
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10. Artificial Intelligence
Frame Representation
Prepared by:
Prof. KhushaliB Kathiriya

11. 3. Frame Representation
ThisconceptwasintroducedbyMarvinMinskyin1975.theyaremostlyused
whenthetaskbecomesquitecomplexandneedsmorestructured
representation.
Morestructuredthesystembecomesmorewouldbetherequirementof
usingframeswhichwouldprovebeneficial.Generallyframesarerecord
likestructuresthatconsistsofacollectionofslotsorattributesandthe
correspondingslotvalues.
Slotscanbeofanysizeandtype.Theslotshavenamesandvaluescalled
asfacts.Facetscanhavenamesornumberstoo.Asimpleframeisshown
infigforpersonram.
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12. 3. Frame Representation (Cont.)
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Ram Brothers Laxman Cat
Bharat
Grey
Color

13. 3. Frame Representation (Cont.)
Sr. No. Slot Value
1 Ram -
2 Profession Professor
3 Age 50
4 Wife Sita
5 Children LuvKush
6 Address 4C gbRoad
7 City Banaras
8 State UP
9 Zip 400615
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14. 3. Frame Representation (Cont.)
Advantages of frame representation:
1.Theframeknowledgerepresentationmakestheprogrammingeasierby
groupingtherelateddata.
2.Theframerepresentationiscomparablyflexibleandusedbymany
applicationsinAI.
3.Itisveryeasytoaddslotsfornewattributeandrelations.
4.Itiseasytoincludedefaultdataandtosearchformissingvalues.
5.Framerepresentationiseasytounderstandandvisualize.
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15. 3. Frame Representation (Cont.)
Disadvantages of frame representation:
1.Inframesysteminferencemechanismisnotbeeasilyprocessed.
2.Inferencemechanismcannotbesmoothlyproceededbyframe
representation.
3.Framerepresentationhasamuchgeneralizedapproach.
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