- calculateConfidenceApproximationFor3Atoms(Rule) - Method in class amie.mining.assistant.MiningAssistant
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Calculate the confidence approximation of the query for the case when the rule has exactly 3 atoms.
- calculateConfidenceApproximationForGeneralCase(Rule) - Method in class amie.mining.assistant.MiningAssistant
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Given a rule with more than 3 atoms and a single path connecting the head variables,
it computes a confidence approximation.
- calculateConfidenceBoundsAndApproximations(Rule) - Method in class amie.mining.assistant.MiningAssistant
-
It computes the confidence upper bounds and approximations for the rule sent as argument.
- calculateConfidenceMetrics(Rule) - Method in class amie.mining.assistant.DefaultMiningAssistant
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- calculateConfidenceMetrics(Rule) - Method in class amie.mining.assistant.MiningAssistant
-
It computes the standard and the PCA confidence of a given rule.
- canAddInstantiatedAtoms() - Method in class amie.mining.assistant.MiningAssistant
-
Returns true if the assistant configuration allows the addition of instantiated atom, i.e., atoms
where one of the arguments has a constant.
- cardinalityForRelation(ByteString) - Method in class amie.rules.Rule
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Returns the number of times the relation occurs in the atoms of the query
- close() - Method in class amie.data.KB.Instantiator
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- colFunctionality(ByteString, KB.Column) - Method in class amie.data.KB
-
Functionality of a relation given the position.
- combineRules(List<Rule>) - Static method in class amie.rules.Rule
-
Given a list of rules A1 => X1, ...
- compress(CharSequence) - Static method in class amie.data.KB
-
Compresses a string to an internal string
- computeBodySize(ByteString, ByteString, Rule) - Method in class amie.mining.assistant.DefaultMiningAssistant
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Returns the number of distinct bindings of the given variables in the body of the rule.
- computeCardinality(Rule) - Method in class amie.mining.assistant.DefaultMiningAssistant
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- computeCardinality(Rule) - Method in class amie.mining.assistant.MiningAssistant
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It computes the number of positive examples (cardinality) of the given rule
based on the evidence in the database.
- computePcaBodySize(ByteString, ByteString, Rule, List<ByteString[]>, ByteString[], int) - Method in class amie.mining.assistant.DefaultMiningAssistant
-
Returns the denominator of the PCA confidence expression for the antecedent of a rule.
- computePCAConfidence(Rule) - Method in class amie.mining.assistant.DefaultMiningAssistant
-
- computePCAConfidence(Rule) - Method in class amie.mining.assistant.MiningAssistant
-
It computes the PCA confidence of the given rule based on the evidence in database.
- computeStandardConfidence(Rule) - Method in class amie.mining.assistant.DefaultMiningAssistant
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- computeStandardConfidence(Rule) - Method in class amie.mining.assistant.MiningAssistant
-
It computes the standard confidence of the given rule based on the evidence in database.
- confidenceMetric - Variable in class amie.mining.assistant.MiningAssistant
-
Confidence metric used to assess the quality of rules.
- ConfidenceMetric - Enum in amie.mining
-
- contains(CharSequence...) - Method in class amie.data.KB
-
It returns TRUE if the database contains this fact (no variables).
- contains(ByteString...) - Method in class amie.data.KB
-
It returns TRUE if the database contains this fact (no variables).
- containsDisallowedDiamond() - Method in class amie.rules.Rule
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- containsHardCase(Rule, ByteString[]) - Method in class amie.mining.assistant.DefaultMiningAssistant
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It determines whether the rule contains an expensive query patterns of the forms
#(x, y) : r(z, x) r(z, y) or #(x, y) : r(y, z) r(x, z).
- containsLevel2RedundantSubgraphs() - Method in class amie.rules.Rule
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For rules with an even number of atoms (n > 2), it checks if it contains
level 2 redundant subgraphs, that is, each relation occurs exactly twice
in the rule.
- containsRelation(ByteString) - Method in class amie.rules.Rule
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- containsRelationTimes(ByteString) - Method in class amie.rules.Rule
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- containsRepeatedVariablesInLastPattern() - Method in class amie.rules.Rule
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Determines if a pattern contains repeated components, which are
considered hard to satisfy (i.e., ?x somePredicate ?x)
- containsSinglePath() - Method in class amie.rules.Rule
-
It determines whether the rule contains a single path that connects the
head variables in the body.
- containsUnifiablePatterns() - Method in class amie.rules.Rule
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Determines whether the last atom of the query.
- containsVariables(List<ByteString[]>) - Static method in class amie.data.KB
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Determines whether a sequence of triples contains at least one variable
- count(CharSequence...) - Method in class amie.data.KB
-
It returns the number of instances (bindings) that satisfy this
triple pattern.
- count(ByteString...) - Method in class amie.data.KB
-
returns number of instances of this triple
- countAlwaysOnSubject - Variable in class amie.mining.assistant.MiningAssistant
-
Count directly on subject or use functional information
- countBindings(int, ByteString...) - Method in class amie.data.KB
-
Counts, for each binding of the variable at position pos, the number of
instantiations of the triple
- countDistinct(CharSequence, List<CharSequence[]>) - Method in class amie.data.KB
-
It returns the number of instantiations of variable that fulfill a certain
list of triple patterns.
- countDistinct(ByteString, List<ByteString[]>) - Method in class amie.data.KB
-
returns the number of instances that fulfill a certain condition
- countDistinctPairs(ByteString, ByteString, List<ByteString[]>) - Method in class amie.data.KB
-
returns the number of distinct pairs (var1,var2) for the query
- countOneVariable(ByteString...) - Method in class amie.data.KB
-
Returns the number of distinct results of the triple pattern query
with 1 variable.
- countPairs(CharSequence, CharSequence, List<ByteString[]>) - Method in class amie.data.KB
-
returns the number of distinct pairs (var1,var2) for the query
- countPairs(ByteString, ByteString, List<ByteString[]>, int[]) - Method in class amie.data.KB
-
- countPairs(ByteString, ByteString, List<ByteString[]>, int[], ByteString[], int) - Method in class amie.data.KB
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- countProjection(CharSequence[], List<CharSequence[]>) - Method in class amie.data.KB
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Counts the number of instances of the projection triple that exist in
joins with the query
- countProjection(ByteString[], List<ByteString[]>) - Method in class amie.data.KB
-
Counts the number of instances of the projection triple that exist in
joins with the other triples
- countProjectionBindings(int, ByteString[], List<ByteString[]>) - Method in class amie.data.KB
-
Counts for each binding of the variable at pos how many instances of the
projection triple exist in the query
- countProjectionBindings(ByteString[], List<ByteString[]>, ByteString) - Method in class amie.data.KB
-
For each instantiation of variable, it returns the number of instances of
the projectionTriple satisfy the query.
- countProjectionBindings(CharSequence[], List<CharSequence[]>, CharSequence) - Method in class amie.data.KB
-
Counts, for each binding of the variable the number of instantiations of
the projection triple
- countTwoVariables(ByteString...) - Method in class amie.data.KB
-
Returns the number of distinct results of the triple pattern query
with 2 variables.