-
公开(公告)号：US11709893B2
公开(公告)日：2023-07-25
申请号：US16685731
申请日：2019-11-15
Inventor： Yan Chen , Kai Liu , Jing Liu , Yajuan Lyu , Qiaoqiao She , Kun Liu
IPC: G06F16/90 , G06F16/9032 , G06N3/02 , G06F16/9538 , G06F16/903 , G06F16/906
CPC classification number: G06F16/90332 , G06F16/906 , G06F16/90324 , G06F16/90335 , G06F16/9538 , G06N3/02
Abstract: The present disclosure provides a search method, an electronic device and a storage medium, and belongs to a technical field of the Internet. The method includes: determining a first set of features corresponding to an original search statement by parsing the original search statement; obtaining each initial search result corresponding to the original search statement; determining a second set of features corresponding to an initial search result by parsing a title of the initial search result; determining a rewritten search statement corresponding to the original search statement and the initial search result by codecing the first set of features and the second set of features; and obtaining a supplementary search result corresponding to the rewritten search statement.
-
公开(公告)号：US11521603B2
公开(公告)日：2022-12-06
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.
-
公开(公告)号：US11847150B2
公开(公告)日：2023-12-19
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
CPC classification number: G06F16/3347 , G06F16/3344 , G06N20/20
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.
-
Patent Agency Ranking
公开(公告)号：US10810272B2
公开(公告)日：2020-10-20
申请号：US15349919
申请日：2016-11-11
Inventor： Kai Liu , Yang Feng , Qin Yang , Yajuan Lyu
IPC: G06F16/9535 , G06F16/35 , G06N5/04 , G06F16/638 , G06F16/2458
Abstract: The present disclosure provides a method and an apparatus for broadcasting a search result based on artificial intelligence. The method includes: receiving a query sentence inputted by a user, and acquiring a plurality of candidate search results according to the query sentence; analyzing each candidate search result to determine a category of each candidate search result, in which the category includes a structured result and a rich-text result; acquiring intention information of the query sentence, and screening the plurality of candidate search results according to the intention information and the category of each candidate search result to obtain a screened search result; and generating text information corresponding to the screened search result, and broadcasting the text information.
-
公开(公告)号：US11842148B2
公开(公告)日：2023-12-12
申请号：US17130299
申请日：2020-12-22
Inventor： Kai Liu
IPC: G06F40/20 , G06N20/00 , G06F40/289
CPC classification number: G06F40/20 , G06N20/00 , G06F40/289
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.
-
6.发明授权公开(公告)号：US11461556B2
公开(公告)日：2022-10-04
申请号：US16886244
申请日：2020-05-28
Inventor： Yuchen Ding , Kai Liu , Jing Liu , Yan Chen
IPC: G06F40/30 , G06F40/258 , G06N3/08 , G09B7/02
Abstract: A method for processing questions and answers 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. Semantic representation vectors obtained through the first semantic representation model of question and the second semantic representation model of question are spliced. A spliced semantic vector is determined as a semantic representation vector of the question to be answered. An answer semantic vector matching the semantic representation vector of the question to be answered is acquired from a vector index library of answer, and an answer corresponding to the answer semantic vector is determined as a target answer to the question to be answered.
-
公开(公告)号：US11704326B2
公开(公告)日：2023-07-18
申请号：US17407272
申请日：2021-08-20
IPC: G06F16/2458 , G06F16/2453 , G06F40/30 , G06N5/02
CPC classification number: G06F16/2468 , G06F16/24534 , G06F40/30 , G06N5/02
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.
-
8.发明授权公开(公告)号：US11410084B2
公开(公告)日：2022-08-09
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.
-
-
-
-
-
-
-
Search Results
8
records
(took 0.018 seconds)
