International Business Machines Corporation

Beijing Baidu Netcom Science and Technology Co., Ltd.

General Electric Company

Beijing Volcano Engine Technology Co., Ltd.

Apple Inc.

Baidu Online Network Technology (beijing) Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

North China Electric Power University

Harbin Engineering University

Shenyang University of Technology

Ke Wei Sun

Shiqi Zhao

Tingting Li

Chao Xue

Shuqi Sun

Haifeng Wang

Rong Yan

Tian Cheng Liu

Junsong Wang

Shuo Li

Yu Meng Li

Ying Li

Lei Han

Yonghua Lin

Dianhai Yu

Jianying Li

Yonggang Hu

Jun Guo

Qing Xu

Chaoyue Wang

Yan Gong

Zhenyu Jiao

Zhihui Sun

Mengjun Li

Boa Hua Yang

Liang Liu

Yu Zhang

Kai Liu

Robert W Schlub

Ying Liu

Jie Zhang

Jing Liu

Lin Y Yang

Chao Wang

Qingxiang Li

Harish Rajagopalan

Rodney Andres Gomez Angulo

Shi Lei Zhang

Qian Ma

Bo Yu

Tao Yu

Andreas Kind

Yong Hua Lin

Huan-Chu Huang

Jie Qiu

Umar Azad

Jingjing Zhang

Zhe Yang

Xiao Zhong

Ju Wang

XiaoYan Yu

Xuan Luo

Chang Chen

Chang Xu

Ning Li

Lin Dong

Lijie Wang

Zhou Xin

Zhi Ye

Peini Liu

Li Mei Jiao

Jian Gong

Xu Pan

Qianqian Wang

Hehan Li

Shuai Gao

Hang Meng

Yongqian Liu

Siqi Xu

Hongjie Guo

Zecheng Zhuo

Zhang Yu

Huifeng Sun

Liyan Yang

Di Wei

Zhiqun Xia

Xiaoxing Wang

Lei Qi

Dianwei Gao

Zhichuan Li

Shuaizheng Wang

Jianhua Zhang

Chao Tang

Zhenlong Yu

Yingzhuo Song

The present application discloses an access limiting method for a metadata server, an apparatus and a device, wherein the method is applied to a data lake metadata server, receives a metadata access request sent by a client, wherein the request is used for obtaining metadata stored by a storage server for describing target data, and the target data is data in a target table. The metadata service interface used by the data lake metadata server is determined according to the metadata access request. When the metadata service interface satisfies the preset condition, determining the number of applied tokens corresponding to the metadata access request according to the number of table partitions and the number of partition levels of the obtained target table.

Access limiting method, apparatus and device for metadata server

A lakehouse metadata tag creation method, a lakehouse metadata tag query method and an electronic device are provided. The method includes: after a metadata service gateway determines a metadata tag creation request based on a metadata tag creation parameter provided by a data engine, sending, by the metadata service gateway, the metadata tag creation request to a metadata tag service system, so that the metadata tag service system executes a tag creation logic based on the metadata tag creation parameter carried in the metadata tag creation request, to implement a requirement of tagging one or more pieces of metadata.

Lakehouse metadata tag creation method, lakehouse metadata tag query method and electronic device

The present application discloses a method and an apparatus for generating a dialogue, and a storage medium. The method includes: obtaining problem information; inputting the problem information to a small sample learning model to generate a first feature; inputting the problem information to a deep learning (DL) model to generate a second feature; combining the first feature and the second feature to generate a feature sequence; and inputting the feature sequence to a fusion model to generate dialogue information corresponding to the problem information.

Method and apparatus for creating dialogue, and storage medium

Provided is a data labeling method based on artificial intelligence, an apparatus, and a storage medium relating to the field of artificial intelligence, particularly data labeling, image recognition, and natural language processing. The method includes: determining a plurality of samples involved in clustering; performing a plurality of following operations circularly to realize iterative processing, until a convergence condition is satisfied or a quantity of iterations reaches a number threshold, comprising: pre-clustering the plurality of samples according to a vector representation of the respective samples to obtain a plurality of class clusters, each class cluster containing at least one sample; receiving labeling information for the respective class clusters and re-determining the plurality of samples according to the labeling information; and determining a clustering result according to the labeling information for the respective class clusters.

Data labeling method based on artificial intelligence, apparatus and storage medium

A one-shot neural architecture search method referred to as MergeNAS by merging different types of convolutions into a single operation. This mergence approach reduces the search cost to roughly half a GPU-day as well as alleviates the over-fitting problem caused by a traditional differentiable architecture search (DARTS) approach by reducing the number of redundant parameters.

Merge operations for darts

A tensegrity offshore wind power generation support structure is provided, relating to the technical field of offshore wind power. The support structure includes inclined columns, prestressed cables, a rigid support, a floating foundation and anchoring systems. A stable self-balancing space supporting structure is formed by the inclined columns and the cables; the inclined columns inclines outwards, upper parts of the inclined columns are connected with the prestressed cables; the bottom ends of the inclined columns are connected with the floating foundation; the middle parts of the inclined columns are connected with the rigid support; and the floating foundation is fixed with a seabed through the anchoring systems. According to the support structure, a tower in the traditional design is not needed, and all the cables are ensured to be in a tension state through the support of the inclined columns.

Tensegrity offshore wind power generation support structure

Aspects of the invention include systems and methods to obtain meta features of a dataset for training in a deep learning application. A method includes selecting an initial search space that defines a type of deep learning architecture representation that specifies hyperparameters for two or more neural network architectures. The method also includes applying a search strategy to the initial search space. One of the two or more neural network architectures are selected based on a result of an evaluation according to the search strategy. A new search space is generated with new hyperparameters using an evolutionary algorithm and a mutation type that defines one or more changes in the hyperparameters specified by the initial search space, and, based on the mutation type, the new hyperparameters are applied to the one of the two or more neural networks or the search strategy is applied to the new search space.

Search space exploration for deep learning

A method and apparatus for building a conversation understanding system based on artificial intelligence, a device and a computer-readable storage medium. In embodiments of the present disclosure, it is feasible to obtain the training feedback information provided by conversation service conducted by the user and the basic conversation understanding system, then according to the training feedback information, perform adjustment processing for a service state of the basic conversation understanding system, to obtain an adjustment state of the basic conversation understanding system. It is possible to perform data merging processing according to the training feedback information and the adjustment state of the basic conversation understanding system, to obtain model training data for building the model conversation understanding system. This method does not require persons to participate in annotation operations of the training data, exhibits simple operations and a high correctness rate, improving the efficiency and reliability of the conversation understanding system.

Method and apparatus for building a conversation understanding system based on artificial intelligence, device and computer-readable storage medium

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.

Automatically generating conference minutes

Embodiments of the present disclosure provide a method and apparatus for outputting analysis abnormality information in a spoken language understanding. The method includes: acquiring first spoken language information and a first analysis result for the first spoken language information; determining whether the first analysis result includes intent information; determining whether the first spoken language information includes a predefined word slot value, in response to determining the first analysis result not including the intent information; and outputting information indicating an existence of an abnormality in the first analysis result, in response to determining the first spoken language information including the predefined word slot value.

Method and apparatus for outputting analysis abnormality information in spoken language understanding

Embodiments of the present disclosure provide a method and apparatus for outputting a structured query sentence. The method may include: acquiring a to-be-converted natural language sentence; inputting the to-be-converted natural language sentence into a pre-trained sequence to sequence model to obtain an action sequence corresponding to the to-be-converted natural language sentence; generating a directed acyclic graph according to the action sequence; and outputting a structured query sentence corresponding to the generated directed acyclic graph according to a preset corresponding relationship between a directed acyclic graph and a structured query sentence.

Method and apparatus for outputting structured query sentence

Techniques for unattended object detection using machine learning are disclosed. A machine learning policy, for use in identifying unattended objects in a captured image depicting one or more objects, is generated. The generating includes determining a level of occlusion in the captured image relating to the objects, and determining the machine learning policy based on the determined level of occlusion. A machine learning model is selected, from among a plurality of pre-defined machine learning models, based on the generated machine learning policy. An unattended object is detected in the captured image using the selected machine learning model.

Unattended object detection using machine learning

The present disclosure discloses a method for generating a question answering robot, relates to the field of robotics. The specific implementation includes: obtaining field information input by a user, obtaining a field-specific robot from a robot library based on the field information; obtaining a template list corresponding to the field-specific robot, providing the template list to the user, the template list including a plurality of templates; receiving the plurality of templates filled in by the user, the templates filled in by the user including at least one question and an answer corresponding to the at least one question; expanding the at least one question filled in by the user based on a question semantic database to form a combination of questions corresponding to the answer, the answer and the combination of questions forming a question-answer pair; and generating a question answering robot based on the question-answer pair.

Method for generating question answering robot and computer device

The present disclosure provides a method and a device for obtaining an answer, and a computer device. The method includes: receiving a question entered by a user; obtaining one or more first key information points in the question entered by the user according one or more preset word slots; asking the user about core question points through dialogue according to the one or more first key information points; obtaining answers entered by the user for the core question points; obtaining one or more second key information points in the answers entered by the user according to the one or more preset word slots; performing a retrieving in a question and answer library according to the one or more first key information points and the one or more second key information points to obtain an answer to the question entered by the user; and presenting the answer obtained to the user.

Method and device for obtaining answer, and computer device

The present disclosure provides a computer-implemented method, computer system and computer program product for object detection. According to the computer-implemented method, a first object can be classified to be a first category based on detection data acquired in a detection area. Then, a confidence score for the first category can be calculated based on historical detection data of the detection area, wherein the confidence score presents possibility degree of at least one object of the first category existing in the detection area. Whether classification of the first object is abnormal can be determined based on the confidence score.

Object detection optimization

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Beijing, China

Ke Wei Sun