公开(公告)号：US10255129B2

公开(公告)日：2019-04-09

申请号：US15292561

申请日：2016-10-13

Applicant: Huawei Technologies Co., Ltd.

Inventor： Xin Jiang ,  Hang Li

IPC: G06F11/00 ,  G06F11/07 ,  G05B23/02 ,  H04L12/24

Abstract: A fault diagnosis method for a big-data network system includes extracting fault information from historical data in the network system, to form training sample data, which is trained to obtain a deep sum product network model that can be used to perform fault diagnosis; and diagnosing a fault of the network system based on the deep sum product network model. The embodiments of the present application resolve a problem that it is difficult to diagnose a fault of a big-data network system.

公开(公告)号：US20180276525A1

公开(公告)日：2018-09-27

申请号：US15993619

申请日：2018-05-31

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Xin Jiang ,  Zhengdong Lu ,  Hang Li

IPC: G06N3/00 ,  G06N3/04 ,  G06F17/27

CPC classification number: G06N3/006 ,  G06F16/3329 ,  G06F17/2715 ,  G06F17/2785 ,  G06N3/0427 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/084

Abstract: A method and neural network system for human-computer interaction, and user equipment are disclosed. According to the method for human-computer interaction, a natural language question and a knowledge base are vectorized, and an intermediate result vector that is based on the knowledge base and that represents a similarity between a natural language question and a knowledge base answer is obtained by means of vector calculation, and then a fact-based correct natural language answer is obtained by means of calculation according to the question vector and the intermediate result vector. By means of this method, a dialog and knowledge base-based question-answering are combined by means of vector calculation, so that natural language interaction can be performed with a user, and a fact-based correct natural language answer can be given according to the knowledge base.

公开(公告)号：US20170102984A1

公开(公告)日：2017-04-13

申请号：US15292561

申请日：2016-10-13

Applicant: Huawei Technologies Co., Ltd.

Inventor： Xin Jiang ,  Hang Li

IPC: G06F11/07

CPC classification number: G06F11/079 ,  G05B23/02 ,  G06F11/0709 ,  G06F11/0751 ,  G06F11/0787 ,  H04L41/0631 ,  H04L41/142

Abstract: A fault diagnosis method for a big-data network system includes extracting fault information from historical data in the network system, to form training sample data, which is trained to obtain a deep sum product network model that can be used to perform fault diagnosis; and diagnosing a fault of the network system based on the deep sum product network model. The embodiments of the present application resolve a problem that it is difficult to diagnose a fault of a big-data network system.