úÎ\oZá     «models a Lattice for a context type, the top of the lattice is represented by One and inherits a list of all subcontexts, the bottom of the lattice is represented by Zero.hahn@geoinfo.tuwien.ac.atbetaNone)347 Tdata type to represent a lattice structure, the actual context is the type variable c›constructor represents the One element of the lattice, all contexts are included in this constructor, for this constructor the model includes all contextsconstructor for one contextMconstructor represents the bottom element of the lattice, without any context]extracts a context list of contexts from the element, needed for the One wrapper constructor0makes a list of contexts for the One constructor%takes a context and returns all finerÿ Checks if the first context list is included in the second, if so the context is returned, so far the function is does not have any order restrictions (is commutative) checks also sublists, if an element of a sublist is in both lists, the whole list is includedtest for commutativityÿø(Ctx [Walking]) `propCommutative` One [Ctx [Walking],Ctx [Driving],Ctx [Walking,Driving],Ctx [Uphill],Ctx [Walking,Uphill],Ctx [Driving,Uphill],Ctx [Walking,Driving,Uphill]] = (Ctx [Walking]) `meet` One [Ctx [Walking],Ctx [Driving],Ctx [Walking,Driving],Ctx [Uphill],Ctx [Walking,Uphill],Ctx [Driving,Uphill],Ctx [Walking,Driving,Uphill]] == One [Ctx [Walking],Ctx [Driving],Ctx [Walking,Driving],Ctx [Uphill],Ctx [Walking,Uphill],Ctx [Driving,Uphill],Ctx [Walking,Driving,Uphill]] `meet` (Ctx [Walking])truetest for idempotencyZpropIdempotent (Ctx [Walking]) = (Ctx [Walking]) `meet` (Ctx [Walking]) == (Ctx [Walking])truetest for associativityÂpropAssociative (Ctx [Walking]) (Ctx [Driving]) (Ctx [Uphill]) = (Ctx [Walking]) `meet` ((Ctx [Driving]) `meet` (Ctx [Uphill])) == ((Ctx [Walking]) `meet` (Ctx [Driving])) `meet` (Ctx [Uphill])true0checks in which level of the lattice the actual  Context c? is One gets level 1, Zero gets level 0, and all others are 1+Omakes the Context c type to a MeetSemiLattice by implementing the meet function *Context where elements are extracted from,extracted context list*list of context c occured by constructor cextracted listcontext that is used as start?all finer contexts of the start context included in the lattice3first list that is used to check against second onesecond list is like a reference(elements that are included in both lists context one context two#true if the property is full-filledcontext to test#true if the property is full-filled context one context two context three#true if the property is full-filled%context to check level in the latticelevel in the lattice   Wconnects the context Lattice with observation frequencies of exemplars using a multisethahn@geoinfo.tuwien.ac.atbetaNone147 Hthe class defines the necessary functions needed for the context algebra <combines the observation amount of exemplars for one contextJIf an experience is made several times the amount can be specified by the amount Ecalculates the amount of experiences that are present for the concept Dunions the experiences stored for one concept for different contexts šfilters a concept for a context, gets a concept for a finer context, the context c has to be more finer than the context that are included in the conceptTreturns a probability of an exemplar observed in a context for the given experiencesqreturns the typicality distribution for each exemplar in the context c, the type e is only used as type parameter9returns the typical exemplar of a concept for the contextAreturns experiences for the exemplar given in the first argument e' in quantum mechanics called projector1converts the experiences of the concept to a IO() adds the new$ experience to the given experiences#type synonym for better readability&All experiences are hold in a multiset`Each experience is formed by a exemplar of type e and a context c this exemplar was observed at.Fconstructor; establishes an experience from a context and an exemplar *context in which the experiences were madeexemplars which are observed7amount of observations for one exemplar in this context,resulting concept with the given experiences)experience that is observed several times(amount of observations of the experience/concept represented by an amount of experiences concept including experincesamount of experiences Elist of conceptualizations holding experiences for different contextsEunion of the experiences holding now all experiences for all contexts &context used to filter the experiencesexperiences to filter9filtered experiences, more finer experiences are returned exemplar and context to look for.concept hoding experiences that are consideredAprobability of the exemplar in this context for the given concept$context the distribution is made for%exemplar type, used as type parameterconcept with the experiencesreturned distribution$context the distribution is made for%exemplar type, used as type parameterconcept with the experiences(tupel with the highest probability value'exemplar used to filter the experiencesconcept that are filtered0concept including experiences for the exemplar e#experiences of the concept to print returned IO()new experience to add-given concept where to add the new experience=resulting concept including the new and the given experiencesnew experience to add-given concept where to add the new experience=resulting concept including the new and the given experiences           !Conte_Ee8Pr5HBQaHGzGhFEkHDagContextLattice ConceptModelContextOneCtxZeroextractContextgetFinerContextspropCommutativepropIdempotentpropAssociativeConceptContextModelcreateConceptForContextamountExperiencesunionsConceptsForDiffContextsfilterConceptWithContexttypicalityForExemplarsInContexttypicalExemplarInContext printConcept ProbabilityConcept ExperienceExpextractOneContextisPartOflevel$fMeetSemiLatticeContextmanyfoldExperiencestypicalityofExemplarInContextfilterExemplars addExperienceforgetExperience