Microsoft Technology Licensing, LLC

Beijing Baidu Netcom Science Technology Co., Ltd

Boe Technology Group Co., Ltd.

Chinese Academy of Sciences

Beijing Baidu Netcom Science and Technology Co., Ltd.

Mianyang Boe Optoelectronics Technology Co., Ltd.

Beijing Ten Dimensions Technology Co., Ltd.

The Procter Gamble Company

Yi Xie

Wei Li

Yang Zhang

Shuangquan Yang

Long Cheng

Chang Liu

Lei Han

Wei Zhou

Yuqing Li

Chao Guo

Xuan Li

Zhen Shen

Li Wan

Feiyue Wang

Gang Xiong

Robert Bao Ha

Hang Gao

Junyi Chen

Keke Zhou

Hsinju Ho

Xiuqin Shang

Dongjian Shi

Meihua Zhao

Guihua Bai

Xisong Dong

Zhengpeng Wu

Robert (bao Ha

The present disclosure provides a method for generating a knowledge graph, a method for mining relation and an apparatus for generating a knowledge graph. The method for generating a knowledge graph includes: obtaining an initial knowledge graph, wherein the initial knowledge graph comprises a plurality of nodes having connection relationships; determining a plurality of target map elements meeting preset property information requirements from the initial knowledge graph, in which the target map elements comprise target nodes, or target edges; and merging the plurality of the target map elements to generate a knowledge graph.

Method and apparatus for generating knowledge graph, method for relation mining

A word mining method and apparatus, an electronic device and a readable storage medium are disclosed. The method includes: acquiring search data; taking first identification information, a search sentence and second identification information in the search data as nodes, and taking a relationship between the first identification information and the search sentence, a relationship between the first identification information and the second identification information and a relationship between the search sentence and the second identification information as sides to construct a behavior graph; obtaining a label vector of each search sentence in the behavior graph according to a search sentence with a preset label in the behavior graph; determining a target search sentence in the behavior graph according to the label vector; and extracting a target word from the target search sentence, and taking the target word as a word mining result of the search data.

Word mining method and apparatus, electronic device and readable storage medium

A pixel structure includes a plurality of first sub-pixels arranged in a first direction and a second direction. A maximum dimension of at least one first sub-pixel in a first direction is less than a first set value, and a maximum dimension of the at least one first sub-pixel in a second direction is greater than a second set value. The first set value is a maximum dimension of a set sub-pixel in the first direction, and the second set value is a maximum dimension of the set sub-pixel in the second direction. The first sub-pixel has an area equal to an area of the set sub-pixel.

Pixel structure, display substrate, mask and evaporation method

The present application discloses a method, an apparatus, a device, and a storage medium for intention recommendation, which relates to the field of big data, artificial intelligence, intelligent search, information flow and deep learning technologies in the field of computer technologies. A specific implementation scheme includes: receiving an intention query request carrying an intention keyword and a user identification, determining a first recommendation list according to the intention keyword and a pre-configured intention repository, where the intention repository includes at least one tree-shaped intention set, and each tree-shaped intention set includes at least one graded intention, processing intentions in the first recommendation list by using intention strategy information corresponding to the user identification to obtain a target recommendation list and output it.

Method, apparatus, device, and storage medium for intention recommendation

The present disclosure discloses a query method, an apparatus, an electronic device, and a storage medium, and relates to the technical field of spatio-temporal big data in big data technologies. The specific implementation scheme is as follows: receiving a query request sent by a terminal device, where the query request is used to request to query dynamic association relationships of a target entity and includes an identifier of the target entity and query starting and ending time; determining at least one time bucket to be queried in a query database according to the query starting and ending time, where each time bucket stores the dynamic association relationships of the target entity in a time period corresponding to the time bucket; and querying the dynamic association relationships of the target entity in the at least one time bucket according to the identifier of the target entity.

Query method, apparatus, electronic device and storage medium

A neural network-based error compensation method for 3D printing includes: compensating an input model by a deformation network/inverse deformation network constructed and trained according to a 3D printing deformation function/inverse deformation function, and performing the 3D printing based on the compensated model. Training samples of the deformation network/inverse deformation network include to-be-printed model samples and printed model samples. The deformation network constructed according to the 3D printing deformation function is marked as a first network. During training of the first network, the to-be-printed model samples are used as real input models, and the printed model samples are used as real output models. The inverse deformation network constructed according to the 3D printing inverse deformation function is marked as a second network. During training of the second network, the printed model samples are used as real input models, and the to-be-printed model samples are used as real output models.

Neural network-based error compensation method, system and device for 3D printing

Content transfer involving a gesture is described. In an implementation, a method is implemented by a mobile communications device that includes recognizing a gesture input via a touchscreen of the mobile communications device that is indicative of a direction, the touchscreen including a display of content. One or more other mobile communications devices are located that are positioned, approximately, along the indicated direction of the gesture. A communication is formed to transfer the content to the located one or more other mobile communications devices.

Content transfer involving a gesture

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Beijing, China

Yi Xie