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A robot data interoperation domain ontology construction method based on depth learning

A technology of deep learning and domain ontology, which is applied in the field of ontology construction in the field of robot data interoperability based on deep learning, can solve problems such as slow construction speed and complex engineering, achieve high efficiency, overcome engineering complexity, and improve industrial robot data interoperability horizontal effect

Inactive Publication Date: 2019-03-29
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

At present, most of the ontologies are manually edited by domain experts, and there are disadvantages such as complex engineering and slow construction speed.

Method used

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  • A robot data interoperation domain ontology construction method based on depth learning
  • A robot data interoperation domain ontology construction method based on depth learning
  • A robot data interoperation domain ontology construction method based on depth learning

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specific Embodiment

[0038] A specific embodiment is: a method for constructing an ontology in the field of robot data interoperability based on deep learning, which mainly includes the following steps:

[0039] a. Acquisition and preprocessing of data sources in the field of robotics;

[0040] b. Term extraction and concept extraction in the field of robotics based on deep learning;

[0041] c. Build a relationship model between robot data and concepts to form a robot domain ontology.

[0042] Preferably, in step a, the robot domain data source acquires source data in various ways such as domain-related knowledge, robot domain-related texts, industrial robot-related international standards, robot domain-related knowledge reports, robot xml data, etc., and constructs a robot domain dictionary. Preprocessing firstly segmented the robot field dictionary, and used the ICTCLAS Chinese lexical analysis system to segment the text data into individual words, and marked the part of speech. The word-segm...

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Abstract

The invention claims a robot data interoperation domain ontology construction method based on depth learning, which comprises the pretreatment of data source, the robot domain term extraction and concept extraction based on depth learning, and the construction of a relationship model between robot data and concept. This method solves the key problem of data interoperability in robot heterogeneoussystems, that is, how to solve the problem of semantic heterogeneity of heterogeneous data sources. This method is mainly applied to data interoperability in manufacturing heterogeneous systems, completes the semi-automatic construction of robot ontology, is the perfection of the existing ontology theory and application research in China, and fills the blind spot of the application research of ontology theory in the field of industrial robots. Compared with the traditional manual method, the ontology construction process is more convenient and quick, and it is suitable for the ontology construction of a large number of data sources.

Description

technical field [0001] The invention belongs to ontology construction technology in the field of manufacturing informatization, belongs to the aspect of robot data interoperability, and in particular relates to an ontology construction method based on deep learning in the field of robot data interoperation. Background technique [0002] With the advent of the information age of the manufacturing industry, information sharing has become an important technology for the development of information technology. However, most manufacturing equipment is only developed for a specific working environment, and some more and more complex tasks require the cooperation of multiple devices to complete. There are many scenarios where various devices work together in industrial sites, but our country’s technical foundation in this area is not strong. With the continuous development of technology, people have put forward higher requirements for data sharing, hoping to eliminate the gap betwee...

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Application Information

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IPC IPC(8): G06F16/36G06F16/35
Inventor 罗志勇于士杰赵杰范志鹏马国喜郑焕平罗蓉蔡婷
Owner CHONGQING UNIV OF POSTS & TELECOMM
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