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公开(公告)号：US12025443B2
公开(公告)日：2024-07-02
申请号：US17410878
申请日：2021-08-24
Inventor： Jizhou Huang , Deguo Xia , Haifeng Wang
CPC classification number: G01C11/06 , G01C21/3859 , G01C21/3885 , G06F16/23 , G06F18/214 , G06N3/08 , G06V20/182
Abstract: The present application discloses a method and apparatus for identifying an updated road, a device and a computer storage medium, and relates to the field of big data technologies. A specific implementation solution is as follows: comparing a road area extracted based on the latest satellite image with a road area extracted based on a historical satellite image, to obtain a candidate updated road; mapping the candidate updated road into road network data according to a coordinate position of the candidate updated road; acquiring a user trajectory set corresponding to the candidate updated road within a recent preset period; and identifying, based on a matching result between the user trajectory set and the road network data, whether the candidate updated road is an actual updated road. Updated roads can be more accurately identified through the method according to the present application.
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公开(公告)号：US11977574B2
公开(公告)日：2024-05-07
申请号：US17754464
申请日：2021-07-20
Inventor： Jizhou Huang , Yibo Sun , Haifeng Wang
IPC: G06F16/387 , G06F40/295
CPC classification number: G06F16/387 , G06F40/295
Abstract: A method and apparatus for acquiring point of interest (POI) state information are suggested, which relate to a big data technology in the technical field of artificial intelligence. A specific implementation scheme involves: acquiring a text including POI information within a preset period from the Internet; and recognizing the text by using a pre-trained POI state recognition model, to obtain a two-tuple in the text, the two-tuple including a POI name and POI state information corresponding to the POI name. The POI state recognition model acquires a vector representation of each first semantic unit in the text, and acquires a vector representation of each second semantic unit in the text based on semantic dependency information of the text; fuses the vector representation of each first semantic unit and the vector representation of each second semantic unit to obtain a fusion vector representation of each first semantic unit; and predicts labels of the POI name and a POI state based on the fusion vector representation of each first semantic unit.
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公开(公告)号：US11928434B2
公开(公告)日：2024-03-12
申请号：US17444693
申请日：2021-08-09
Inventor： Jiachen Liu , Xinyan Xiao , Hua Wu , Haifeng Wang
IPC: G06F40/56 , G06F40/295 , G06N5/022 , G06N20/00
CPC classification number: G06F40/295 , G06N5/022 , G06N20/00 , G06F40/56
Abstract: A method for text generation, relates to a field of natural language processing, including: obtaining corpus data; labeling the corpus data to obtain a first constraint element; obtaining a first generation target; and generating a first text matching the first generation target by inputting the corpus data and the first constraint element into a generation model.
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公开(公告)号：US11328133B2
公开(公告)日：2022-05-10
申请号：US16585269
申请日：2019-09-27
Inventor： Hao Xiong , Zhongjun He , Xiaoguang Hu , Hua Wu , Zhi Li , Zhou Xin , Tian Wu , Haifeng Wang
Abstract: The present disclosure provides a translation processing method, a translation processing device, and a device. The first speech signal of the first language is obtained, and the speech feature vector of the first speech signal is extracted based on the preset algorithm. Further, the speech feature vector is input into the pre-trained end-to-end translation model for conversion from the first language speech to the second language text for processing, and the text information of the second language corresponding to the first speech signal is obtained. Moreover, speech synthesis is performed on the text information of the second language, and the corresponding second speech signal is obtained and played.
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公开(公告)号：US20210390257A1
公开(公告)日：2021-12-16
申请号：US17116846
申请日：2020-12-09
Inventor： Chao Pang , Shuohuan Wang , Yu Sun , Hua Wu , Haifeng Wang
IPC: G06F40/295 , G06F40/30 , G06F40/137 , G06N5/02
Abstract: A method, an apparatus, a device and a storage medium for learning a knowledge representation are provided. The method can include: sampling a sub-graph of a knowledge graph from a knowledge base; serializing the sub-graph of the knowledge graph to obtain a serialized text; and reading using a pre-trained language model the serialized text in an order in the sub-graph of the knowledge graph, to perform learning to obtain a knowledge representation of each word in the serialized text. The knowledge representation learning in this embodiment is performed for entity and relationship representation learning in the knowledge base.
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Patent Agency Ranking
公开(公告)号：US11157698B2
公开(公告)日：2021-10-26
申请号：US16176783
申请日：2018-10-31
Inventor： Jizhou Huang , Yaming Sun , Wei Zhang , Haifeng Wang
IPC: G06F40/00 , G06F40/295 , G06F16/951 , G06K9/00 , G06K9/62 , G06N7/00 , G06F40/30 , G06F40/268 , G06F40/242
Abstract: The present disclosure provides a method of training a descriptive text generating model, and a method and apparatus for generating a descriptive text, wherein the method of training a descriptive text generating model comprises: obtaining training data, the training data comprising: a notional word, a first descriptive text and a second descriptive text of the notional word, wherein the second descriptive text is a concise expression of the first descriptive text; regarding the notional word and the first descriptive text of the notional word as input of a seq2seq model, regarding the second descriptive text of the notional word as output of the seq2sequ model, and training the seq2seq model to obtain a descriptive text generating model. The descriptive text generating model according to the present disclosure can implement generation of a concise descriptive text with respect to the notional word in a deep understanding manner.
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公开(公告)号：US11132518B2
公开(公告)日：2021-09-28
申请号：US16691111
申请日：2019-11-21
Inventor： Chuanqiang Zhang , Tianchi Bi , Hao Xiong , Zhi Li , Zhongjun He , Haifeng Wang
Abstract: A method and apparatus for translating speech are provided. The method may include: recognizing received to-be-recognized speech of a source language to obtain a recognized text; concatenating the obtained recognized text after a to-be-translated text, to form a concatenated to-be-translated text; inputting the concatenated to-be-translated text into a pre-trained discriminant model to obtain a discrimination result for characterizing whether the concatenated to-be-translated text is to be translated, where the discriminant model is used to characterize a corresponding relationship between a text and a discrimination result corresponding to the text; in response to the positive discrimination result being obtained, translating the concatenated to-be-translated text to obtain a translation result of a target language, and outputting the translation result.
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公开(公告)号：US11126639B2
公开(公告)日：2021-09-21
申请号：US15409967
申请日：2017-01-19
Inventor： Haifeng Wang , Wei He , Yu Ma , Weide Zhang , Liming Xia , Zhuo Chen
IPC: G06F17/00 , G06F7/00 , G06F16/27 , B60R16/023
Abstract: This present application discloses a method and apparatus for synchronizing data in a robot operating system. A specific implementation of the method includes: detecting an operation on data being transmitted between communication processes, wherein the operation includes at least one of updating the data, deleting the data, and storing the data; determining whether the data are persistent data, in response to positively detecting an operation on the data being transmitted between the communication processes; and transmitting a change message of the data to communication processes other than the communication processes in response to positively determining that the data are persistent data. In the embodiment, the persistent data may always remain consistent across the communication processes.
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9.发明申请公开(公告)号：US20180357571A1
公开(公告)日：2018-12-13
申请号：US16006213
申请日：2018-06-12
Inventor： Ke Sun , Shiqi Zhao , Dianhai Yu , Haifeng Wang
CPC classification number: G06N99/005 , G06F7/14 , G06F17/2785
Abstract: A conversation processing method and apparatus based on artificial intelligence, a device and a computer-readable storage medium. The disclosure embodiments, enable the user feedback information provided by conversation service conducted by the user to model conversation understanding system, then according to the user feedback information, perform adjustment processing for a service state of the model conversation understanding system, to obtain an adjustment state of the model conversation understanding system so that it is possible to execute the conversation service with the model conversation understanding system, based on the adjustment state. Since a fault-tolerant and fault-correcting mechanism is provided, it is possible to adjust the understanding capability of the model conversation understanding system in real time and thereby effectively improve the reliability of conversation by collecting the user's user feedback information, and then adjusting the service state of the model conversation understanding system in time based on the user feedback information.
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公开(公告)号：US20180067878A1
公开(公告)日：2018-03-08
申请号：US15409930
申请日：2017-01-19
Inventor： Jingchao Feng , Liming Xia , Quan Wang , Ning Qu , Zhuo Chen , Yu Ma , Haifeng Wang , Yibing Liang
IPC: G06F13/16 , G06F12/1072 , G06F12/02
CPC classification number: G06F13/1663 , G06F12/023 , G06F12/084 , G06F12/0842 , G06F12/1072 , G06F2212/1044
Abstract: The present application discloses a method and an apparatus for transmitting information. A specific implementation of the method includes: sending first information to be transmitted to a shared memory; traversing memory groups in the shared memory, and acquiring a first memory unit suitable for the amount of the first information, each of the memory groups including at least one memory unit, each of memory units in the memory group having an identical size, and the memory units in different memory groups having different sizes; and storing the first information into the acquired first memory unit, so that the first information is read from the first memory unit by a receiving node. Through this implementation, the first information that needs to be transmitted is stored into the memory unit suitable for the amount of the first information, thereby saving memory resources.
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