公开(公告)号：US20180336206A1

公开(公告)日：2018-11-22

申请号：US15981334

申请日：2018-05-16

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Shengxian WAN ,  Yu SUN ,  Dianhai YU

IPC: G06F17/30 ,  G06F17/27 ,  G06K9/62 ,  G06N5/04

Abstract: The present disclosure provides a method and apparatus for evaluating a matching degree based on artificial intelligence, a device and a storage medium, wherein the method comprises: respectively obtaining word expressions of words in a query and word expressions of words in a title; respectively obtaining context-based word expressions of words in the query and context-based word expressions of words in the title according to the word expressions; generating matching features according to obtained information; determining a matching degree score between the query and the title according to the matching features. The solution of the present disclosure may be applied to improve the accuracy of the evaluation result.

公开(公告)号：US20210357814A1

公开(公告)日：2021-11-18

申请号：US17362674

申请日：2021-06-29

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Xinxuan WU ,  Xuefeng YAO ,  Dianhai YU ,  Zhihua WU ,  Yanjun MA ,  Tian WU ,  Haifeng WANG

IPC: G06N20/00

Abstract: The present disclosure provides a method and apparatus for distributed training a model, an electronic device, and a computer readable storage medium. The method may include: performing, for each batch of training samples acquired by a distributed first trainer, model training through a distributed second trainer to obtain gradient information; updating a target parameter in a distributed built-in parameter server according to the gradient information; and performing, in response to determining that training for a preset number of training samples is completed, a parameter exchange between the distributed built-in parameter server and a distributed parameter server through the distributed first trainer to perform a parameter update on the initial model until training for the initial model is completed.

公开(公告)号：US20180357225A1

公开(公告)日：2018-12-13

申请号：US16005779

申请日：2018-06-12

Applicant: Beijing Baidu Netcom Science And Technology Co., Ltd.

Inventor： Yi LIU ,  Daxiang DONG ,  Dianhai YU

IPC: G06F17/28 ,  H04L12/58 ,  G06F17/27 ,  G06N3/04 ,  G06F17/18

Abstract: Embodiments of the present disclosure relate to a method for generating chatting data based on AI, a computer device and a computer-readable storage medium. The method includes: converting chatting data inputted by a user into an input word sequence; converting a tag of the user into a tag word sequence; based on a preset encoding-decoding model with an attention model, predicting according to the input word sequence and the tag word sequence to obtain a target word sequence; and converting the target word sequence into reply data of the chatting data.

公开(公告)号：US20180341698A1

公开(公告)日：2018-11-29

申请号：US15990157

申请日：2018-05-25

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Shuohuan WANG ,  Yu SUN ,  Dianhai YU

IPC: G06F17/30 ,  G06F17/27 ,  G06N5/02 ,  G06N99/00

Abstract: The present disclosure provides a method and apparatus for parsing a query based on artificial intelligence, and a storage medium, wherein the method comprises: regarding any application domain, obtaining a knowledge library corresponding to the application domain; determining a training query serving as a training language material according to the knowledge library; obtaining a deep query parsing model by training according to the training language material; using the deep query parsing model to parse the user's query to obtain a parsing result. The solution of the present disclosure may be applied to improve the accuracy of the parsing result.

公开(公告)号：US20210374542A1

公开(公告)日：2021-12-02

申请号：US17444687

申请日：2021-08-09

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Wenhui ZHANG ,  Dianhai YU ,  Zhihua WU

IPC: G06N3/08 ,  G06F8/65

Abstract: The invention discloses a method and an apparatus for updating parameters of a multi-task model. The method includes: obtaining a training sample set, in which the training sample set comprises a plurality of samples and a task to which each sample belongs; putting each sample into a corresponding sample queue sequentially according to the task to which each sample belongs; training a shared network layer in the multi-task model and a target sub-network layer of tasks associated with the sample queue with samples in the sample queue in case that the number of the samples in the sample queue reaches a training data requirement, so as to generate a model parameter update gradient corresponding to the tasks associated with the sample queue; and updating parameters of the shared network layer and the target sub-network layer in a parameter server according to the model parameter update gradient.

公开(公告)号：US20180349512A1

公开(公告)日：2018-12-06

申请号：US16000160

申请日：2018-06-05

Applicant: Beijing Baidu Netcom Science and Technology Co., Ltd.

Inventor： Zhiliang TIAN ,  Daxiang DONG ,  Dianhai YU

IPC: G06F17/30 ,  G06N5/02

Abstract: A method and apparatus for recalling news based on artificial intelligence, a device and a storage medium. The method comprises: building an index repository according to candidate news, the index repository including M search trees, each search tree being a complete binary tree including at least two layers, each non-leaf node in each search tree corresponding to a semantic index vector, each piece of candidate news corresponding to a leaf node in each search tree; when news needs to be recommended to the user, generating a user's semantic index vector according to the user's interest tag; with respect to each search tree, respectively according to semantic index vectors corresponding to non-leaf nodes therein and the user's semantic index vector, determining a path from a first layer of non-leaf nodes to a leaf node, and regarding candidate news corresponding to the leaf node on the path as a recall result.