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公开(公告)号：US20220179858A1
公开(公告)日：2022-06-09
申请号：US17407272
申请日：2021-08-20
IPC: G06F16/2458 , G06F16/2453 , G06N5/02 , G06F40/30
Abstract: The present disclosure provides a generalization processing method, apparatus, device and computer storage medium, and relates to technical field of artificial intelligence and specifically to a deep learning technique. A specific implementation solution is: determining a set of candidate queries in a query library that are similar to a requested query in at least one of a literal matching manner, a semantic matching manner and a query rewriting manner; determining a generalized query corresponding to the requested query from the set of candidate queries by using a pre-trained query matching model; wherein the query matching model is obtained by pre-training based on a cross attention model. The generalization for the requested query can be achieved according to the present disclosure.
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公开(公告)号：US20210407499A1
公开(公告)日：2021-12-30
申请号：US17061353
申请日：2020-10-01
Inventor： Ke SUN , Ying LIU , Kai LIU , Lei HAN , Chao WANG , Yingzhuo SONG , Shuai GAO , Liyan YANG , Qianqian WANG , Jing LIU , Di WEI
IPC: G10L15/183 , G10L15/26 , H04L12/18
Abstract: A conference minutes generation method is provided, which relates to the technical field of natural language processing. The conference minutes generation method comprises: acquiring a text conference record; dividing the text conference record into a plurality of conference paragraphs, generating a conference paragraph summary for each conference paragraph, and generating a conference record summary based on the conference paragraph summary of each conference paragraph; extracting conference instructions based on the text conference record; and generating the conference minutes based on the conference record summary and the conference instructions.
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公开(公告)号：US20210374195A1
公开(公告)日：2021-12-02
申请号：US16951889
申请日：2020-11-18
IPC: G06F16/951 , G06F16/958 , G06F16/9535
Abstract: The present disclosure provides an information processing method, an electronic device and a computer storage medium, and relates to a field of information processing. The method includes: obtaining a first content based on a first search keyword indicating a first event and a second search keyword indicating an object related to the first event; obtaining information associated with an attribute of the object from the first content; obtaining a second content based on the first search keyword and a third search keyword indicating a result at least caused by the first event; and generating statistical data associated with the first event based on the information and the second content.
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公开(公告)号：US20180352043A1
公开(公告)日：2018-12-06
申请号：US15942276
申请日：2018-03-30
Inventor： Hao LIU , Kai LIU , Yajuan LYU
Abstract: The present disclosure discloses an artificial intelligence based method and apparatus for pushing news. A specific embodiment of the method includes: determining at least one news subject from a news text of to-be-pushed news; extracting, from the news text, text fragments respectively associated with news subjects; generating, for each of the news subjects, a subject tag based on the extracted text fragment through a deep learning method; and pushing the to-be-pushed news based on the at least one news subject and the generated subject tag. This embodiment may improve the effectiveness of news pushing.
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Patent Agency Ranking
公开(公告)号：US20210383062A1
公开(公告)日：2021-12-09
申请号：US17130299
申请日：2020-12-22
Inventor： Kai LIU
Abstract: The present disclosure discloses a method for training a reading comprehension model, and relates to a field of natural language processing and deep learning technologies. The detailed implementing solution includes: respectively inputting a first training sample of the reference field into a reference reading comprehension model of a reference field and a target reading comprehension model of a target field, to obtain first output data output by the reference reading comprehension model and second output data output by the target reading comprehension model; and performing a first training process on the target reading comprehension model based on a difference between the first output data and the second output data.
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公开(公告)号：US20180336193A1
公开(公告)日：2018-11-22
申请号：US15942330
申请日：2018-03-30
Abstract: The present disclosure discloses an artificial intelligence based method and apparatus for generating an article. A specific embodiment of the method comprises: acquiring predetermined structure data for generating an article; generating candidate sentences from the predetermined structure data using a sentence generation model; forming a chapter by splicing candidate sentences selected according to a probability for a sentence containing a preset information point appearing, wherein each time a candidate sentence is selected, candidate sentences relating to the selected candidate sentence are excluded according to a preset exclusion rule; and generating an article based on the chapter formed by splicing, in response to no candidate sentence being available.
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公开(公告)号：US20220100786A1
公开(公告)日：2022-03-31
申请号：US17407320
申请日：2021-08-20
Inventor： Yuchen DING , Yingqi QU , Jing LIU , Kai LIU , Dou HONG , Hua WU , Haifeng WANG
Abstract: The present application discloses a method and apparatus for training a retrieval model, device and computer storage medium that relate to intelligent search and natural language processing technologies. An implementation includes: acquiring initial training data; performing a training operation using the initial training data to obtain an initial retrieval model; selecting texts with the correlation degrees with a query in the training data meeting a preset first requirement from candidate texts using the initial retrieval model; performing a training operation using the updated training data to obtain a first retrieval model; and selecting texts with the correlation degrees with the query in the training data meeting a preset second requirement from the candidate texts using the first retrieval model; and/or selecting texts with the correlation degrees with the query meeting a preset third requirement; and performing a training operation using the expanded training data to obtain a second retrieval model.
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8.发明申请公开(公告)号：US20210201196A1
公开(公告)日：2021-07-01
申请号：US16915885
申请日：2020-06-29
Inventor： Kai LIU , Qiaoqiao SHE
IPC: G06N20/00 , G06F40/242 , G06F17/16
Abstract: Embodiments of the present disclosure provide a method and an apparatus for training a machine reading comprehension model, and a storage medium. The method includes: training an initial model to generate an intermediate model based on sample data; extracting samples to be processed from the sample data according to a first preset rule; generating a noise text according to a preset noise generation method; adding the noise text to each of the samples to be processed respectively to generate noise samples; and performing correction training on the intermediate model based on the noise samples to generate the machine reading comprehension model.
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9.发明申请公开(公告)号：US20210200956A1
公开(公告)日：2021-07-01
申请号：US16886244
申请日：2020-05-28
Inventor： Yuchen DING , Kai LIU , Jing LIU , Yan CHEN
IPC: G06F40/30 , G09B7/02 , G06F40/258 , G06N3/08
Abstract: The present disclosure discloses a method and an apparatus for processing questions and answers, an electronic device and a storage medium. The implementation solution includes: in a process of determining an answer to a question to be answered, determining the semantic representation on the question to be answered respectively with a first semantic representation model of question and a second semantic representation model of question, splicing semantic representation vectors obtained through the first semantic representation model of question and the second semantic representation model of question, determining a spliced semantic vector as a semantic representation vector of the question to be answered, acquiring an answer semantic vector matching the semantic representation vector of the question to be answered from a vector index library of answer, and determining an answer corresponding to the answer semantic vector as a target answer to the question to be answered.
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