Complex design knowledge network construction method based on multi-source data mining

Abstract

The invention provides a complex design knowledge network construction method based on multi-source data mining, which comprises the following steps of: firstly, considering the design of a network top layer model, and aiming at the problems of poor consistency, weak availability, low sharing rate and the like of multi-source data of internal and external systems of a manufacturing enterprise, extracting entities and relationships from the multi-source data by using dependency syntactic analysis; and constructing a knowledge network top layer model. Before top nodes of a knowledge network are matched with design knowledge, the design knowledge needs to be organized and arranged, and the design knowledge is divided into different design knowledge items according to characteristics of multi-domain data to construct a design knowledge representation model. On the basis, the top layer model and the design knowledge are linked and matched, and a complex design knowledge network in a field is established. According to the method, a'unified expression-efficient organization-standardization 'system of design knowledge is designed, inspiration and help are provided for the design process by utilizing multi-domain data, design knowledge and clues are found for designers, a knowledge-driven design technology is realized, and the product innovation ability of manufacturing enterprises is improved.

Description

technical field [0001] The invention relates to a complex design knowledge network construction method based on multi-source data mining, which belongs to the research content of big data knowledge engineering in the field of artificial intelligence. Background technique [0002] With the rapid development of big data technology and artificial intelligence, how to make full use of data and design knowledge in manufacturing enterprises is the most critical issue. dimensional data), it is necessary to consider how to effectively process these massive multi-source heterogeneous data, and use multi-domain data to help designers find design knowledge clues and realize knowledge-driven design technology. However, large and complex product manufacturing enterprises in the manufacturing industry have massive disordered and repetitive data, coupled with the limitations of human cognition and memory, in many cases, designers cannot accurately locate the required design knowledge when ...

AI Technical Summary

Problems solved by technology

Aiming at the problems of poor consistency, weak usability, and low sharing rate of multi-source heterogeneous data in the internal and external systems of manufacturing enterprises, the triplet method is used to extract entities and relationships from multi-domain data, and a top-level knowledge network model is constructed.

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