Automatic updating of a combine harvester knowledge-based system by webpages and user-uploaded files

Currently, knowledge-based systems are generally updated manually, resulting in long cycles, low efficiency, and difficulty in ensuring comprehensive and systematic supplementary content. To address this issue, a knowledge-based system automatic updating method based on webpage information and user files is proposed for combine harvesters. The knowledge storage structure in an electronic warehouse is analyzed, and knowledge and data types are determined. A crawler designed to locate the combine harvester-related information in the target webpage realizes the acquisition and sorting of webpage knowledge and data. The type of file uploaded by the user is set based on the knowledge base and data type; the content of the user file is extracted and filtered, and the knowledge and data of the knowledge-based system are user-defined. The organized knowledge and data are stored or updated in the knowledge base to achieve automatic updating of the knowledge-based system based on webpage information and user files. The test results show that based on user file updates, the knowledge and data of the knowledge-based system can be customized according to user needs. This meets user requirements and allows for effective automatic updates based on webpages after automatic updating of the knowledge base based on webpages. After the automatic updating of the knowledge base based on webpage information is triggered, the knowledge and data from the three webpages that were initially crawled and read are automatically updated to the knowledge base in 5.265 s. Realizing the automatic updating of knowledge and data can shorten the updating period, maintain the effectiveness and practicability of the knowledge-based system, ensure the scientific and advanced nature of the intelligent design process, and provide technical models and methods for the knowledge collection of similar knowledge-based systems.