Part information query method and system

Abstract

The invention discloses a part information query method and system. The query method comprises the steps of receiving a part information query request, and obtaining part query information and a vehicle identification number (VIN) carried in the query request; translating the part query information into part standard names; screening out all part information matched with the part standard names according to a preset part association relationship; and finding out the part information matched with the VIN in all the part information. Through the part information query method and system provided by the invention, all systems are connected for part information query, so that a free, convenient, fast and intelligent part query mode can be realized and the intelligence, accuracy and efficiency of part query are improved.

Description

technical field [0001] The invention relates to the technical field of auto parts query, in particular to a method and system for querying parts information. Background technique [0002] The spare parts information system in the current automobile market is fragmented. Automobile manufacturers, parts manufacturers, maintenance companies, and insurance companies each apply their own systems and standards, and the systems cannot communicate. [0003] As far as the parts query methods in the current spare parts market are concerned, most of them follow the spare parts query system of automobile manufacturers. The name of the part is completely matched, and intelligent query cannot be achieved; and in terms of development methods, there are few big data development models, which are more dependent on human development, so the development accuracy and timeliness are not good. [0004] Therefore, there is an industry problem that needs to be solved urgently to have a way to conn...

AI Technical Summary

Problems solved by technology

[0002] The spare parts information system in the current automobile market is fragmented. Automobile manufacturers, parts manufacturers, maintenance companies, and insurance companies each apply their own systems and standards, and there is no communication between the systems.

[0003] As far as the parts query methods in the current spare parts market are concerned, most of them follow the spare parts query system of automobile manufacturers. The name of the part is completely matched, and intelligent query cannot be achieved; and in terms of development methods, there are few big data development models, which are more dependent on human development, so the development accuracy and timeliness are not good.

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