Ontology Query Inference Approximation Method Based on Minimal Explanation
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An approximation method, the smallest technology, applied in electrical digital data processing, special data processing applications, complex mathematical operations, etc.
What is AI technical title?
AI technical title is built by PatSnap AI team. It summarizes the technical point description of the patent document.
An approximation method, the smallest technology, applied in electrical digital data processing, special data processing applications, complex mathematical operations, etc.
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[0022] Professor Gottlob and others published the paper "Ontological Queries: Rewriting and Optimization" in the ICDE2011 International Database Engineering Conference, and proposed an accurate method for query reasoning in the datalog± ontology. This method exhaustively invokes two types of rules to apply (applicability) rules and factorizability (factorizability) rules, rewrite the input joint query into multiple new queries according to the TBox part of the given datalog± ontology, and then pass these new queries Directly access the ABox part of the given datalog ontology to get the respective set of query answers. The union of these query answer sets is equal to the answer set for a given query. Since the new query obtained by rewriting may contain an infinite number of atoms, this method cannot guarantee that for any given datalog± ontology, the query answer can be completed within a finite time.
[0023] The present invention has carried out the following transformation...
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Abstract
The invention relates to an ontology query reasoning approximation method based on minimal explanation, which belongs to the field of artificial intelligence. The applicable object of the method is the datalog± ontology with strong expressive ability and wide application range. It is characterized in that the query for the datalog± ontology is automatically converted into a set of minimum interpretations whose length does not exceed the threshold specified by the user, and then directly accesses the ABox part of the ontology through each minimum interpretation to obtain the respective query answer sets. The union of these sets is a subset of the original query answer set, and its closeness to the original set is controlled by the minimum interpretation length threshold. The key to the method is to automatically compile the TBox part of the datalog± ontology into a Prolog program that can receive joint queries from users, and invoke the efficient Prolog system to automatically calculate all the minimum explanations whose length does not exceed the threshold specified by the user. The overall data complexity of the method is polynomial time. The invention is applicable to various application occasions based on datalog± ontology, and provides efficient information query service for these occasions.
Description
technical field [0001] The invention relates to an approximation method for ontology query reasoning based on minimal explanation, belongs to the field of artificial intelligence, and is suitable for query reasoning on large-scale datalog± ontology. Background technique [0002] The current increasingly popular World Wide Web has entered the Web 3.0 era, and its core part is the Semantic Web, which aims to provide some mechanisms for computers to understand and process web pages. Ontology, as the foundation of the Semantic Web, has been increasingly valued by academic fields such as artificial intelligence and software engineering. Ontologies are explicit representations of concepts. From the perspective of artificial intelligence, ontology can be expressed as the logical relationship between entities. At present, there are more and more applications based on ontology, especially in the field of biomedicine, a number of practical applications using large-scale domain ontol...
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