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公开(公告)号：US11637570B2
公开(公告)日：2023-04-25
申请号：US17320636
申请日：2021-05-14
发明人： Liang Ma , Hang Li , Yuejun Wei
IPC分类号： H03M13/45
摘要： One example method includes obtaining L1 first decoding paths of an (i−1)th group of to-be-decoded bits, where i is an integer, received data corresponds to P groups of to-be-decoded bits, and 1
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公开(公告)号：US11500954B2
公开(公告)日：2022-11-15
申请号：US16538174
申请日：2019-08-12
IPC分类号： G06F16/9538 , G06N20/00
摘要： A learning-to-rank method based on reinforcement learning, including obtaining, by a server, a historical search word, and obtaining M documents corresponding to the historical search word; ranking, by the server, the M documents to obtain a target document ranking list; obtaining, by the server, a ranking effect evaluation value of the target document ranking list; using, by the server, the historical search word, the M documents, the target document ranking list, and the ranking effect evaluation value as a training sample, and adding the training sample into a training sample set.
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公开(公告)号：US11308405B2
公开(公告)日：2022-04-19
申请号：US16514683
申请日：2019-07-17
发明人： Lifeng Shang , Zhengdong Lu , Hang Li
IPC分类号： G06N5/04 , G06F16/332 , G10L13/08 , G10L15/22 , G06F40/35 , G06F16/33 , H04L12/58 , H04L51/02
摘要： An apparatus is pre-equipped with a plurality of dialogue robots, and each dialogue robot is configured to conduct a human-computer dialogue based on at least one topic. The method includes: obtaining a text entered by a user; determining at least one topic related to the text, and determining a target dialogue robot from the plurality of dialogue robots based on the at least one topic related to the text and a predefined mapping relationship between a dialogue robot and a topic, where a target topic corresponding to the target dialogue robot is some or all of the at least one topic related to the text; and allocating the text to the target dialogue robot and obtaining a reply for the text from the target dialogue robot, where the reply is generated by the target dialogue robot based on at least one semantic understanding of the text.
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公开(公告)号：US11138385B2
公开(公告)日：2021-10-05
申请号：US16672092
申请日：2019-11-01
发明人： Zhengdong Lu , Hang Li
IPC分类号： G06F40/30 , G06N3/04 , G06F16/36 , G06F40/284
摘要： A method and an apparatus for determining a semantic matching degree, where the method includes acquiring a first sentence and a second sentence, dividing the first sentence and the second sentence into x and y sentence fragments, respectively, performing a convolution operation on word vectors in each sentence fragment of the first sentence and word vectors in each sentence fragment of the second sentence to obtain a three-dimensional tensor, performing integration or screening on adjacent vectors in the one-dimensional vectors of x rows and y columns, until the three-dimensional tensor is combined into a one-dimensional target vector, and determining a semantic matching degree between the first sentence and the second sentence according to the target vector.
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公开(公告)号：US11132516B2
公开(公告)日：2021-09-28
申请号：US16396172
申请日：2019-04-26
发明人： Zhaopeng Tu , Lifeng Shang , Xiaohua Liu , Hang Li
摘要： A sequence conversion method includes receiving a source sequence, converting the source sequence into a source vector representation sequence, obtaining at least two candidate target sequences and a translation probability value of each of the at least two candidate target sequences according to the source vector representation sequence, adjusting the translation probability value of each candidate target sequence, selecting an output target sequence from the at least two candidate target sequences according to an adjusted translation probability value of each candidate target sequence, and outputting the output target sequence. Hence, loyalty of a target sequence to a source sequence can be improved during sequence conversion.
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公开(公告)号：US11025768B2
公开(公告)日：2021-06-01
申请号：US16993426
申请日：2020-08-14
发明人： Simon Ekstrand , Hang Li , Zhiming Fan , Xueyan Huang , Zewen Li , Sha Qian , Shouyu Wang
IPC分类号： H04M1/72442 , G06F3/0481 , H04M1/72469
摘要： An information displaying method and a terminal are provided. The method includes: obtaining audio data to be played in a chronological order; determining, based on attribute information at any moment of a sound represented by the audio data, a shape of a graph corresponding to the any moment, where the graph corresponding to the any moment including a closed curve with a bump, and a maximum distance in distances from points on the bump to a center of the graph is positively correlated to a value indicated by the attribute information at the any moment; and displaying the graph corresponding to the any moment. The bump in the graph changes with the value indicated by the attribute information of the sound, and such graph is presented to a user, to enhance perception of the user on the attribute information of the audio data and improve user experience.
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公开(公告)号：US20200065388A1
公开(公告)日：2020-02-27
申请号：US16672092
申请日：2019-11-01
发明人： Zhengdong Lu , Hang Li
摘要： A method and an apparatus for determining a semantic matching degree, where the method includes acquiring a first sentence and a second sentence, dividing the first sentence and the second sentence into x and y sentence fragments, respectively, performing a convolution operation on word vectors in each sentence fragment of the first sentence and word vectors in each sentence fragment of the second sentence to obtain a three-dimensional tensor, performing integration or screening on adjacent vectors in the one-dimensional vectors of x rows and y columns, until the three-dimensional tensor is combined into a one-dimensional target vector, and determining a semantic matching degree between the first sentence and the second sentence according to the target vector.
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公开(公告)号：US10255129B2
公开(公告)日：2019-04-09
申请号：US15292561
申请日：2016-10-13
摘要： 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.
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公开(公告)号：US20190018836A1
公开(公告)日：2019-01-17
申请号：US16134393
申请日：2018-09-18
IPC分类号： G06F17/27
摘要： A word segmentation method and system for a language text, where in the method, a word segmentation is performed on the first language text in a first word segmentation manner to obtain a first word boundary set, the first word boundary set is divided into a trusted second word boundary set and an untrusted third word boundary set according to a confidence level threshold, a second language text is selected from the first language text according to the third word boundary set, and a word segmentation is performed on the second language text in a second word segmentation manner to obtain a fourth word boundary set. Word segmentation precision of the first language text can be flexibly adjusted by adjusting the confidence level threshold.
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公开(公告)号：US20180276525A1
公开(公告)日：2018-09-27
申请号：US15993619
申请日：2018-05-31
发明人： Xin Jiang , Zhengdong Lu , Hang Li
CPC分类号： G06N3/006 , G06F16/3329 , G06F17/2715 , G06F17/2785 , G06N3/0427 , G06N3/0445 , G06N3/0454 , G06N3/084
摘要： 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.
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