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公开(公告)号：US20210406767A1
公开(公告)日：2021-12-30
申请号：US17142822
申请日：2021-01-06
Inventor： Daxiang DONG , Weibao GONG , Yi LIU , Dianhai YU , Yanjun MA , Haifeng WANG
IPC: G06N20/00 , G06F16/182 , G06N5/04
Abstract: The present application discloses a distributed training method and system, a device and a storage medium, and relates to technical fields of deep learning and cloud computing. The method includes: sending, by a task information server, a first training request and information of an available first computing server to at least a first data server; sending, by the first data server, a first batch of training data to the first computing server, according to the first training request; performing, by the first computing server, model training according to the first batch of training data, sending model parameters to the first data server so as to be stored after the training is completed, and sending identification information of the first batch of training data to the task information server so as to be recorded; wherein the model parameters are not stored at any one of the computing servers.
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2.发明申请公开(公告)号：US20190306274A1
公开(公告)日：2019-10-03
申请号：US16282438
申请日：2019-02-22
Inventor： Baohua LAI , Yukun ZHANG , Long YAN , Hao SONG , Yi LIU , Minghua LI , Hai ZENG
IPC: H04L29/08
Abstract: A distributed database transaction processing method and device based on a GPS atomic clock, the method includes: receiving a plurality of transaction requests by the first node server; determining a concurrency conflict between transaction requests received by the first node server; obtaining start time of each transaction in a case that the concurrency conflict exists, wherein the start time is local time of the second node server when the transaction request is sent; and local time of the second node server is synchronized with time of the GPS atomic clock server in an area which the second node server locates; processing all transactions by the first node server according to the sequence of the start time of each transaction. Throughput of distributed database system can be increased and an arrangement complexity of servers is reduced.
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Patent Agency Ranking
公开(公告)号：US20220114218A1
公开(公告)日：2022-04-14
申请号：US17279377
申请日：2020-06-09
Inventor： Tianjian HE , Yi LIU , Daxiang DONG , Yanjun MA , Dianhai YU
IPC: G06F16/901 , G06F9/30 , G06N3/08
Abstract: A session recommendation method, a device and an electronic device are provided, related to the field of graph neural network technology. The session recommendation method includes: acquiring a session control sequence, and acquiring a first embedding vector matrix based on an embedding vector of each of items in the session control sequence; generating a position information sequence based on an arrangement sequence of the items in the session control sequence, and acquiring a second embedding vector matrix based on an embedding vector of each piece of position information in the position information sequence; determining a target embedding vector matrix based on the first embedding vector matrix and the second embedding vector matrix; and determining a recommended item, based on the target embedding vector matrix and through a Session-based Recommendation Graph Neural Network.
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4.发明申请公开(公告)号：US20210374356A1
公开(公告)日：2021-12-02
申请号：US17399016
申请日：2021-08-10
Inventor： Tianjian HE , Yi LIU , Daxiang DONG , Dianhai YU , Yanjun MA
Abstract: The disclosure discloses a conversation-based recommending method. A directed graph corresponding to a current conversation is obtained. The current conversation includes clicked items, the directed graph includes nodes and directed edges between the nodes, each node corresponds to a clicked item, and each directed edge indicates relationship data between the nodes. For each node of the directed graph, an attention weight is determined for each directed edge corresponding to the node based on a feature vector of the node and the relationship data for each node of the directed graph. A new feature vector of the node is determined based on the relationship data and the attention weight of each directed edge. A feature vector of the current conversation is determined based on the new feature vector of each node. An item is recommended based on the feature vector of the current conversation.
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公开(公告)号：US20190065506A1
公开(公告)日：2019-02-28
申请号：US16054842
申请日：2018-08-03
Inventor： Yukun LI , Yi LIU , Yu SUN , Dianhai YU
Abstract: Embodiments of the present disclosure disclose a search method and apparatus based on artificial intelligence. A specific implementation of the method comprises: acquiring at least one candidate document related to a query sentence; determining a query word vector sequence corresponding to a segmented word sequence of the query sentence, and determining a candidate document word vector sequence corresponding to a segmented word sequence of each candidate document in the at least one candidate document; performing a similarity calculation for each candidate document in the at least one candidate document; selecting, in a descending order of similarities between the candidate document and the query sentence, a preset number of candidate documents from the at least one candidate document as a search result.
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公开(公告)号：US20180329886A1
公开(公告)日：2018-11-15
申请号：US15900176
申请日：2018-02-20
Inventor： Yukun LI , Yi LIU , Yu SUN , Dianhai YU
CPC classification number: G06F17/2785 , G06F17/277 , G06N3/0454 , G06N3/0481 , G06N3/08
Abstract: An artificial intelligence based method and apparatus for generating information are disclosed. The method in an embodiment includes: segmenting a to-be-processed text into characters to obtain a character sequence; determining a character vector for each character in the character sequence to generate a character vector sequence; generating a plurality of character vector subsequences by segmenting the character vector sequence based on a preset vocabulary; for each generated character vector subsequence, determining a sum of character vectors composing the character vector subsequence as a target vector, and inputting the target vector into a pre-trained first neural network to obtain a word vector corresponding to the each character vector subsequence, the first neural network used to characterize a correspondence between the target vector and the word vector; and analyzing the to-be-processed text based on the obtained word vector to generate an analysis result. This embodiment improves the adaptability of text processing.
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7.发明申请公开(公告)号：US20180357225A1
公开(公告)日：2018-12-13
申请号：US16005779
申请日：2018-06-12
Inventor： Yi LIU , Daxiang DONG , Dianhai YU
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.
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