5 results about "Product issues" patented technology

The invention discloses a product quality problem solution automatic generation method and device, a medium and a product, and relates to the field of data processing. The method comprises the steps that a fault code and product type information of a current product quality problem are determined as a target fault code and target product type information, the fault code comprises multiple pieces of fault identification information, and the fault identification information comprises failure part information, failure position information and failure mode information; determining a first recommended solution set from a historical database based on the target fault code and the target product type information; when the data size of the first recommended solution set is insufficient, a second recommended solution set is determined from a historical database based on the fault identification information, and the data size of the second recommended solution set is larger than that of the first recommended solution set; and finally, generating a quality problem recommendation solution based on the second recommendation solution set. The problem that the formulating efficiency of the product problem solution is not high can be relieved.

The invention discloses an after-sales product technical service problem processing method, device and equipment system, relates to the technical field of computers, and solves the problems that the problem processing efficiency is low due to insufficient communication caused by limited experience and frequent personnel replacement when field engineers solve product problems; the method comprises the following steps: submitting product problem information to a server through a mobile terminal, and judging whether the server stores the corresponding product problem information or not; related processing personnel select a processing flow and a related product responsibility unit according to the product problem information, and the responsibility unit edits a problem analysis processing report according to the processing flow; judging whether the problem analysis processing report passes internal verification approval or not; judging whether a corresponding product problem is solved or not; if yes, generating a product problem tracking report, feeding back the product problem tracking report to the server, displaying the product problem tracking report on the mobile terminal, and marking the problem state of the corresponding product as being processed; if not, an early warning signal is sent out; according to the invention, the accuracy and efficiency in the process of processing product problems are improved.

The invention discloses a visual question and answer processing method and system, and the method comprises the steps: presetting a knowledge graph of a product, analyzing dialogue information to determine a problem appeal of a user for the product, extracting a series of frames most related to the problem appeal from a longer product problem video according to the problem appeal and the knowledge graph of the product, and carrying out the analysis of the series of frames. And then generating a short video with a short duration by using the frame, and synchronously displaying the short video and the problem appeal. When the method is applied, when an e-commerce customer service receives a long product problem video, the e-commerce customer service does not need to watch the product problem video and can accurately grasp the appeal of a user for the product problem by watching the corresponding short video, so that accurate data support is provided for accurately and timely answering the user, precious time is won, and the user experience is improved. And the reply timeliness and quality of the e-commerce customer service are greatly improved.

This invention discloses a multi-level and self-learning analysis method and medium for testing data. The method includes: acquiring and parsing product testing result data, and creating a general intelligent agent for the parsed data; determining the type of product problem based on the general intelligent agent, creating a corresponding specialized intelligent agent according to the problem type, and assigning the product problem to at least one corresponding specialized intelligent agent; establishing at least one attribution model based on the specialized intelligent agents to perform in-depth causal analysis of the product testing data and outputting the product reasoning chain; and performing hierarchical self-learning analysis of the product problem based on the reasoning chain and an accumulated knowledge base to obtain key factors affecting the product and the correlation between these factors. This application improves the depth and accuracy of product problem analysis by assigning data to general and specialized intelligent agents, with the general intelligent agent identifying the problem type and the specialized intelligent agents conducting in-depth analysis and mining to output the product reasoning chain.

The present invention discloses a visual question-answering processing method and system, including a knowledge graph of a preset product, analyzing the dialogue information to determine the user's problem demands for the product, extracting a series of frames most relevant to the problem demands from a longer product problem video based on the problem demands and the product's knowledge graph, and then using the above frames to generate a short video with a shorter duration, and synchronously displaying the short video and the problem demands. When the present invention is applied, when an e-commerce customer service receives a longer product problem video, it does not need to watch the product problem video. By watching the corresponding short video, the user's demand for the product problem can be accurately grasped, thereby providing accurate data support for accurate and timely replies to users and winning valuable time, greatly improving the timeliness and quality of the e-commerce customer service's response.