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Data ontology logical reasoning method based on inductive logic program design

A technology of ontology and data, applied in the field of logical reasoning, can solve problems such as lack of processing methods

Inactive Publication Date: 2019-11-15
厦门美域中央信息科技有限公司
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Problems solved by technology

ILP is an interdisciplinary field of machine learning and logic programming. With the help of the existing theories and methods of logic programming, under the framework of first-order logic, it tries to overcome the problems existing in traditional machine learning and establish a new machine learning system. Machines can better simulate human thinking; it is very important to obtain inference results in the field of data technology, but there is a lack of corresponding processing methods in the existing technology

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  • Data ontology logical reasoning method based on inductive logic program design

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Embodiment Construction

[0023] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are exemplary only, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.

[0024] Such as figure 1 As shown, a kind of data ontology logical reasoning method based on inductive logic programming proposed by the present invention includes the following specific steps:

[0025] S1. Preprocessing the data ontology that needs logical reasoning;

[0026] S2. Extracting the subject, predicate and object in the data ontology;

[0027] S3. Transform the data ontology into clauses according to the sub...

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Abstract

The invention discloses a data ontology logical reasoning method based on inductive logic program design. The method comprises the following specific steps: preprocessing a data ontology needing logical reasoning; extracting subjects, predicates and objects in the data ontology; converting the data ontology into clauses according to subjects, predicates and objects extracted from the data ontology; establishing a set of clauses; determining a specified discourse domain A; determining Helbland explanation for each clause in the clause set to obtain different discourse domains B; comparing the discourse domain B with the discourse domain A to determine a final discourse domain range C; processing based on the discourse domain range C to obtain an inference result. According to the method, the data ontology is preprocessed, the discourse domain range is determined through clause and Helbrinde explanation, and then the reasoning result is obtained based on the conclusion principle and theinverse conclusion principle.

Description

technical field [0001] The invention relates to the technical field of logical reasoning methods, in particular to a data ontology logical reasoning method based on inductive logic programming. Background technique [0002] Inductive Logic Programming (ILP) is an inductive method based on first-order logic, which uses an inverse resolution (Inverse Resolution) process. Inductive logic programming ILP can generate new predicates, so it is called constructive induction; learning is a manifestation of human intelligence and a basic way to acquire knowledge or skills, and machine learning is an important manifestation of computer system intelligence. How to make computers better simulate human thinking and learn better is a matter of great concern to scientists and logicians in the computer field. In the current artificial intelligence research, a large number of knowledge engineering practices have shown that the problem of knowledge acquisition is the main obstacle to the imp...

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Application Information

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IPC IPC(8): G06F16/36G06F17/27G06N5/04
CPCG06N5/04G06F16/367
Inventor 刘家祥
Owner 厦门美域中央信息科技有限公司
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