Media transduction type identification method and device, electronic equipment and storage medium

A recognition method and media technology, applied in neural learning methods, electrical digital data processing, biological neural network models, etc., can solve problems such as difficult and deep semantic features, and achieve improved recognition performance, more multi-level feature representation, and information interaction. more diverse effects

Pending Publication Date: 2022-07-29
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Embodiments of the present invention provide a method, device, electronic device, and storage medium for identifying media citation types, so as to solve the technical problem that it is difficult to model deep semantic features contained in different citation types in the prior art

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  • Media transduction type identification method and device, electronic equipment and storage medium
  • Media transduction type identification method and device, electronic equipment and storage medium
  • Media transduction type identification method and device, electronic equipment and storage medium

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Embodiment Construction

[0027] In order to make those skilled in the art better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only The embodiments are part of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the scope of protection of the present application. It should be noted that the embodiments in the present application and the features of the embodiments may be combined with each other in the case of no conflict.

[0028] It should be noted that the terms "first", "second", etc. in the description and claims of the present application and the above drawings are used to disting...

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Abstract

The invention discloses a media transduction type identification method and device, electronic equipment and a storage medium, and belongs to the field of natural language processing. The method comprises the following steps: inputting source information published by a source media and transduction information published by a transduction media into a pre-training language model, and respectively obtaining a chapter representation vector and a sentence representation vector of the source information and the transduction information; performing bidirectional interactive semantic information learning on each sentence representation vector of the source information and the transduction information to obtain a bidirectional interactive semantic chapter representation vector; fusing the chapter representation vector obtained based on the pre-training language model and the interactive semantic chapter representation vector to obtain an enhanced semantic representation vector; and identifying a media transduction type according to the enhanced semantic representation vector to obtain the media transduction type. According to the invention, the semantic representation capability of the chapter is enhanced in a multi-level and fine-grained manner, and the identification performance of the media transduction type is effectively improved.

Description

technical field [0001] The present invention relates to the technical field of natural language processing, and in particular, to a method, device, electronic device and storage medium for identifying a media citation type. Background technique [0002] The identification of media citation types aims to analyze the citation patterns between pairs of information that have a citation relationship. Accurately identifying the citation relationship can help to characterize the communication model from multiple perspectives, gain an in-depth insight into the evolution of information dynamic communication, and provide decision support for the management department to perceive social hotspots in a forward-looking manner. [0003] In existing research, (YaoR, Li Q, Wang L, et al.A novel neural approach for newsreprint prediction[C] / / 2019 International Joint Conference on Neural Networks(IJCNN).IEEE,2019:1-8.), (Li Q, Liu H, Yao R, et al. Entity Mattersin News: AnAssociation Network-...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/30G06F40/253G06F40/211G06N3/04G06N3/08
CPCG06F40/30G06F40/211G06F40/253G06N3/04G06N3/08
Inventor 李秋丹王林子任亚俊彭鑫曾大军
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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