Rules - Documentation

new Rules(maximalDepthopt, traceopt, traceOutputopt)

Description:

Implements a VSA based inference mechanism.

Inference rules are typically defined using such macro construction:

 class MyRules: public Rules {
 public:
 MyRules() : Rules() {
  // ClassInheritance
  Rule_2(rdfs9_,
	     // getTau()
	     return algo::conj(algo::sim(predicate_1, "rdf::type"), algo::sim(object_1, subject_2), algo::sim(predicate_2, "rdfs:subClassOf"));,
	     // setOutput() : please note that *subject_1 and other triple references are pointer prefixed with '*'
	     output.add(*subject_1, tau, "rdfs:type", *object_2);
	     );
  ../.. // Here defining other rules in Rules() constructor.
  }
} myRules;

where Rule_1, Rule_2 and Rule_3 allows to specifies rules of arity 1, 2 ou 3, with as syntax of the form:

Rule_i(ruleName, getTau_return_expression, setOutput_add_instruction);

Parameters:

Name Type Attributes Default Description

Name	Type	Attributes	Default	Description
`maximalDepth`	uint	<optional>	`0`	Maximal number of recursion, i.e.,of reintroducing produced rule output as incoming input, 0 means unbounded.
`trace`	String	<optional>	`"ado"`	Defines the inference trace log, using a combination of chars. 'a' : Dumps applied valid rules application. 'u' : Dumps unapplied invalid rules application. 'd' : Dumps the depth value when starting the inference. 'i' : Dumps incoming triples before each recursion step. 'o' : Dumps output triples produces a each recursion step.
`traceOutput`	String	<optional>	`"stdout"`	defines the trace target: "stdout": The stdout during the inference mechanism. filename : A `filename.log` file saves at the end of the inference mechanism.

maximalDepth

uint

0

Maximal number of recursion,

i.e.,of reintroducing produced rule output as incoming input, 0 means unbounded.

trace

String

"ado"

Defines the inference trace log, using a combination of chars.

'a' : Dumps applied valid rules application.
'u' : Dumps unapplied invalid rules application.
'd' : Dumps the depth value when starting the inference.
'i' : Dumps incoming triples before each recursion step.
'o' : Dumps output triples produces a each recursion step.

traceOutput

String

"stdout"

defines the trace target:

"stdout": The stdout during the inference mechanism.
filename : A filename.log file saves at the end of the inference mechanism.

Methods

add(rule)

Description:

Adds a new rule to the mechanism.

A typical manual construction of a rule is of the form:

class MyRule: public Rule {
public:
  // Defines the rule name and arity
  MyRule() : Rule("name", arity) {}
  // Implements the proper tau calculation mechanism.
  virtual Belief getTau(const Symbol& subject_1, const Symbol& predicate_1, const Symbol& object_1, const Symbol& subject_2, const Symbol& predicate_2, const Symbol& object_2) {
  return ../..
}
  // Implements the proper triple generation mechanism.
  void setOutput(RelationalMap& output) {
    output.add( ../..
  }
};
static MyRule myRule;
rules.add(myRule);

Parameters:

Name Type Description

Name	Type	Description
`rule`	Rule	The rule to add. Since a pointer to the rule is stored, the rule must never be deleted, e.g. a static variable.

rule

Rule

The rule to add.

Since a pointer to the rule is stored, the rule must never be deleted, e.g. a static variable.

isDifferent(subject_1, predicate_1, object_1, subject_2, predicate_2, object_2) → {bool}

Description:

Checks if two triples are distinguishable.
- This method is to be overloaded to implement a specific difference criterion.
- The default implementations calculates the conjunction:
`(subject_1 . subject_2) ^ (predicate_1 . predicate_2) ^ (object_1 . object_2)`
and considers the triples as different if `tau < sigma` for the obtained belief. - Then, it considers the system as incremental and if not different, checks if the 1st triplet brings more information, i.e. if `tau_1 > tau_2 + 2 sigma`, `tau_i` being the product of the triple elements tau values..

Parameters:

Name	Type	Description
`subject_1`	Symbol	The 1st triple subject.
`predicate_1`	Symbol	The 1st triple predicate.
`object_1`	Symbol	The 1st triple object.
`subject_2`	Symbol	The 2nd triple subject.
`predicate_2`	Symbol	The 2nd triple predicate.
`object_2`	Symbol	The 2nd triple object.

Returns:

Returns true if the two triples are distinguishable, or if the 1st triplet brings more information.

Type: bool

apply(triples, incoming)

Description:

Applies recursively the rules on a set of incoming triples given a set of reference triples.
- The relational map reference is enriched by the incoming triples and all their infered consequences.

Parameters:

Name	Type	Description
`triples`	RelationalMap	A relational map reference with triples for rule application with the given triple.
`incoming`	RelationalMap	A relational map reference with triples incoming the inference mechanism.