公开(公告)号：US20250013675A1

公开(公告)日：2025-01-09

申请号：US18653885

申请日：2024-05-02

Applicant: MASHANG CONSUMER FINANCE CO., LTD.

Inventor： Hongyu ZHAO ,  Bing XIAO ,  Kexin LI ,  Mingyao YANG

IPC: G06F16/332 ,  G06F16/35 ,  G06F40/289 ,  G06F40/35

Abstract: A question-mining method includes obtaining a pre-built standard question database, where the standard question database includes a first standard question text, the first standard question text corresponds to a first intent category, and the first standard question text comprises a plurality of words; mining keywords of the first intent category from the plurality of words according to an importance degree of each word of the first standard question text to the first intent category, wherein the plurality of words include the keywords and non-keywords; determining a co-occurrence word of the keywords according to co-occurrence information of the keywords and the non-keywords in the standard question database; and mining a target question text from a pre-obtained target text set according to the co-occurrence word of the keywords.

公开(公告)号：US20240427821A1

公开(公告)日：2024-12-26

申请号：US18824490

申请日：2024-09-04

Applicant: MaShang Consumer Finance Co., Ltd.

Inventor： Hongyu ZHAO ,  Guoqing ZHAO ,  Ning JIANG ,  Bing XIAO

IPC: G06F16/906 ,  G06F16/901

Abstract: The present application provides a data processing method, a category identification method and a computer device, in which, firstly, node information is screened out based on node edge data and feature information, that is, K first nodes with rich structures and high feature discrimination are located, and then a feature similarity is calculated based on relevant information of the first nodes. On the other hand, since a calculation amount of the feature similarity of the node is relatively small, for a case that model training and prediction of node category are completed at the same time, a second node can include a node to be classified, and a model parameter used in category prediction is obtained by performing parameter iterative updating with taking the node to be classified as an unlabeled node.

公开(公告)号：US20250021888A1

公开(公告)日：2025-01-16

申请号：US18897862

申请日：2024-09-26

Applicant: MaShang Consumer Finance Co., Ltd.

Inventor： Hongyu ZHAO

IPC: G06N20/00 ,  G06F40/279

Abstract: The present application relates to a model training method and an apparatus. The model training method includes: processing a text in a corpus to obtain a plurality of samples, where the plurality of samples includes a plurality of positive samples and a plurality of negative samples; building a plurality batches of training sets; inputting each batch of training set into a model for training, and obtaining a category of each sample in each batch of training set; and obtaining an overall loss value according to label information and the category corresponding to each sample, a sample quantity and an overall loss function in each batch of training set, and adjusting the model according to the overall loss value to obtain a trained model.