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1.发明申请公开(公告)号：US20230075339A1
公开(公告)日：2023-03-09
申请号：US18056137
申请日：2022-11-16
Inventor： Zeyang LEI , Xinchao XU , Wenquan WU , Zhengyu Niu
IPC: G06F40/40 , G06F40/284
Abstract: The present disclosure provides a method of training an information generation model, a method of generating an information, an electronic device, and a storage medium. A specific implementation solution of the method of training the information generation model includes: splitting a description information for a target object in an information pair into at least one description word, so as to obtain a description word sequence, wherein the information pair further includes a first recommendation information; inputting the description word sequence into a dialog generation model to obtain a probability vector sequence for the target object, wherein each probability vector in the probability vector sequence includes probability values for a plurality of predetermined words; and training the dialog generation model according to the probability vector sequence and the first recommendation information, so as to obtain the information generation model.
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公开(公告)号：US20230088445A1
公开(公告)日：2023-03-23
申请号：US18059386
申请日：2022-11-28
Inventor： Zeming LIU , Hao LIU , Zhengyu Niu , Hua WU , Haifeng WANG , Hui XIONG
Abstract: A conversational recommendation method, a method of training a conversational recommendation model, an electronic device, and a storage medium are provided, which are related to a technical field of data processing, in particular to technical fields of voice interaction, deep learning, artificial intelligence and the like. The conversational recommendation method includes: acquiring a historical conversation information; determining a target conversation object to be generated, from a conversation target graph based on the historical conversation information, the conversation target graph includes an object node, the object node is configured to represent a conversation object, and the target conversation object is determined based on the object node; and generating a target conversation information for recommendation based on the target conversation object.
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公开(公告)号：US12118319B2
公开(公告)日：2024-10-15
申请号：US17655772
申请日：2022-03-21
Inventor： Jun Xu , Zeming Liu , Zeyang Lei , Zhengyu Niu , Hua Wu , Haifeng Wang
Abstract: The present disclosure provides a dialog method and system, an electronic device and a storage medium, and relates to the field of artificial intelligence (AI) technologies such as deep learning and natural language processing. A specific implementation scheme involves: rewriting a corresponding dialog state based on received dialog information of a user; determining to-be-used dialog action information based on the dialog information of the user and the dialog state; and generating a reply statement based on the dialog information of the user and the dialog action information. According to the present disclosure, the to-be-used dialog action information can be determined based on the dialog information of the user and the dialog state; and then the reply statement is generated based on the dialog action information, thereby providing an efficient dialog scheme.
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公开(公告)号：US20230029687A1
公开(公告)日：2023-02-02
申请号：US17655772
申请日：2022-03-21
Inventor： Jun Xu , Zeming Liu , Zeyang Lei , Zhengyu Niu , Hua Wu , Haifeng Wang
Abstract: The present disclosure provides a dialog method and system, an electronic device and a storage medium, and relates to the field of artificial intelligence (AI) technologies such as deep learning and natural language processing. A specific implementation scheme involves: rewriting a corresponding dialog state based on received dialog information of a user; determining to-be-used dialog action information based on the dialog information of the user and the dialog state; and generating a reply statement based on the dialog information of the user and the dialog action information. According to the present disclosure, the to-be-used dialog action information can be determined based on the dialog information of the user and the dialog state; and then the reply statement is generated based on the dialog action information, thereby providing an efficient dialog scheme.
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