fuzzy_dl_owl2.fuzzydl.query.min.min_related_query

A query mechanism that determines the minimum degree to which two individuals are related through a specific role within a fuzzy description logic knowledge base.

Description

The software implements a specialized query for fuzzy description logic ontologies, specifically designed to compute the minimum membership degree of a role assertion between two distinct individuals. By leveraging mixed-integer linear programming, the system constructs an optimization problem where the objective is to minimize the degree variable associated with the relationship. To ensure the integrity of the original data, the process operates on a cloned instance of the knowledge base, allowing for the addition of temporary assertions and constraints without side effects. The logic involves transforming the role relationship into a concept expression, integrating it into the solver, and handling potential ontology inconsistencies by returning a specific status rather than raising an error.

Classes

MinRelatedQuery

Represents a query that retrieves the minimum degree to which two individuals are related through a specific role within a knowledge base. To use this class, instantiate it with the two individuals and the role name, then invoke the solve method with a KnowledgeBase instance. Internally, the query clones the knowledge base to avoid side effects, constructs a corresponding concept expression, and utilizes mixed-integer linear programming to optimize and determine the minimum membership degree of the role assertion. The result is encapsulated in a Solution object, which accounts for potential inconsistencies in the ontology.

Module Contents

UML Class Diagram for MinRelatedQuery — UML Class Diagram for **MinRelatedQuery**

class MinRelatedQuery( a: fuzzy_dl_owl2.fuzzydl.individual.individual.Individual, b: fuzzy_dl_owl2.fuzzydl.individual.individual.Individual, role_name: str, )[source]

Bases: fuzzy_dl_owl2.fuzzydl.query.related_query.RelatedQuery

Inheritance diagram of fuzzy_dl_owl2.fuzzydl.query.min.min_related_query.MinRelatedQuery

Represents a query that retrieves the minimum degree to which two individuals are related through a specific role within a knowledge base. To use this class, instantiate it with the two individuals and the role name, then invoke the solve method with a KnowledgeBase instance. Internally, the query clones the knowledge base to avoid side effects, constructs a corresponding concept expression, and utilizes mixed-integer linear programming to optimize and determine the minimum membership degree of the role assertion. The result is encapsulated in a Solution object, which accounts for potential inconsistencies in the ontology.

Parameters:

ind1 (Individual) – The first individual involved in the role assertion, representing the subject of the relationship.
ind2 (Individual) – The target individual in the role assertion, corresponding to ‘b’ in the query (min-related? a b R).
role (str) – The name of the role or relationship type connecting the two individuals.

__str__() → str[source]

Returns a human-readable string representation of the query object. The output is formatted as a question asking whether the first individual is related to the second individual through a specific role, followed by a ‘ >= ‘ operator. This method is primarily used for debugging or displaying the current state of the query parameters.

Returns:: A string representation of the object, formatted as a question asking if ind1 is related to ind2 through role.
Return type:: str

preprocess(kb: fuzzy_dl_owl2.fuzzydl.knowledge_base.KnowledgeBase) → None[source]

Prepares the query for execution by constructing a HasValueConcept based on the query’s role and secondary individual, and integrating it into the provided KnowledgeBase. It retrieves a MILP variable representing the degree of membership of the primary individual in this concept and sets the query’s objective expression to target this variable. The method adds assertions to the knowledge base to link the individual to both the concept and its negation, enforcing a constraint where the degree of the negation is derived from the degree of the concept. As a side effect, it increments the knowledge base’s counter for legacy variables and enables dynamic blocking if the concept involves existential restrictions. Finally, it triggers the solving of all added assertions to update the solver’s state.

Parameters:: kb (KnowledgeBase) – The knowledge base instance containing the MILP model, used to retrieve variables, add assertions, and trigger solving.

solve(kb: fuzzy_dl_owl2.fuzzydl.knowledge_base.KnowledgeBase) → fuzzy_dl_owl2.fuzzydl.milp.solution.Solution[source]

Executes the optimization process for the query using the provided Knowledge Base. The method initiates timing, modifies the input Knowledge Base by incrementing its binary variable counter, and resolves the ABox. A clone of the Knowledge Base is then preprocessed and optimized according to the query’s objective expression to generate a solution. If the ontology is found to be inconsistent during this process, the method catches the exception and returns a solution indicating inconsistency rather than raising an error.

Parameters:: kb (KnowledgeBase) – The knowledge base containing the ontology and constraints to be solved and optimized.
Returns:: The Solution object resulting from the optimization of the knowledge base, or a specific status indicating the ontology is inconsistent.
Return type:: Solution

ind1: fuzzy_dl_owl2.fuzzydl.individual.individual.Individual

ind2: fuzzy_dl_owl2.fuzzydl.individual.individual.Individual

role: str