Beijing Baidu Netcom Science and Technology Co., Ltd.

Chinese Academy of Sciences

Beijing Baidu Netcom Science Technology Co., Ltd

Zhijie Liu

Qi Wang

Yong Zhu

Zhifan Feng

Chunguang Chai

Wei He

Long Cheng

Min Tan

Zengguang Hou

Zhou Fang

Zhengxing Wu

Junzhi Yu

Siqi Wang

Hongjun Yang

Tairen Sun

A theme classification method based on multimodality is related to a field of a knowledge map. The method includes obtaining text information and non-text information of an object to be classified. The non-text information includes at least one of visual information and audio information. The method also includes determining an entity set of the text information based on a pre-established knowledge base, and then extracting a text feature of the object based on the text information and the entity set. The method also includes determining a theme classification of the object based on the text feature and a non-text feature of the object.

Theme classification method based on multimodality, device, and storage medium

A method, apparatus, device, and storage medium for linking an entity, relates to the technical fields of knowledge graph and deep learning are provided. The method may include: acquiring a target text; determining at least one entity mention included in the target text and a candidate entity corresponding to each entity mention; determining an embedding vector of each candidate entity based on the each candidate entity and a preset entity embedding vector determination model; determining context semantic information of the target text based on the target text and each embedding vector; determining type information of the at least one entity mention; and determining an entity linking result of the at least one entity mention, based on the each embedding vector, the context semantic information, and each type information.

Method, apparatus, device, and storage medium for linking entity

A method, apparatus, device, and storage medium for entity linking is disclosed. The method includes: acquiring a target text; determining at least one entity mention included in the target text; determining a candidate entity corresponding to each of the entity mention based on a preset knowledge base; determining a reference text of each of the candidate entity and determining additional feature information of each of the candidate entity; and determining an entity linking result based on the target text, each of the reference text, and each piece of the additional feature information, wherein determining the entity linking result includes determining a probability of linking each of the candidate entity to the entity mention based on a splicing of a first embedding vector and a second embedding vector of the target text and a splicing of a first embedding vector and a second embedding vector of each respective reference text.

Method, electronic device, and storage medium for entity linking by determining a linking probability based on splicing of embedding vectors of a target and a reference text

The present disclosure provides a method, a device, an equipment and a storage medium for mining a topic concept. The method includes: acquiring a plurality of candidate topic concepts based on a query; performing word segmentation on the plurality of candidate topic concepts and performing part-of-speech tagging on words obtained after performing the word segmentation, to obtain a part-of-speech sequence of each of the plurality of candidate topic concepts; and filtering the plurality of candidate topic concepts based on the part-of-speech sequence, to filter out a topic concept corresponding to a target part-of-speech sequence among the plurality of candidate topic concepts, in which a proportion of accurate topic concepts in the target part-of-speech sequence is lower than or equal to a first preset threshold, or a proportion of inaccurate topic concepts in the target part-of-speech sequence is higher than or equal to a second preset threshold.

Method, device, equipment, and storage medium for mining topic concept

A control method, system and device for a flexible carbon cantilever beam actuated by a smart material is provided. The new control method, system and device aims to solve the problems of control overflow and instability that are likely to occur in the distributed parameter system constructed in the prior art. The method includes: acquiring an elastic displacement of the flexible carbon cantilever beam in real time as input data; and obtaining, based on the input data, a control torque through a distributed parameter model constructed in advance, and performing vibration control on the flexible carbon cantilever beam. The new control method, system and device improves the control accuracy and stability of the distributed parameter system.

Control method for flexible carbon cantilever beam actuated by smart material

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Beijing, China

Zhijie Liu