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Analysis of automatic news segmentation combining with conditional random field knowledge recognition algorithm

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Abstract

With the continuous development of the social economy, the ways people obtain news information are becoming increasingly diversified, but with that comes too much data. The research on Extracting useful information from too much data is extremely effective. Given these needs and deficiencies, this paper introduces a conditional random field knowledge recognition algorithm, designing a Segmentation analysis model for audience news with the segmentation technology of key frames and shots by sorting the business logic of automatic news Segmentation, realizing the analysis of the news video picture., and then analyze the news Segmentation to ensure that the production and dissemination of news programs are intelligent and smart. The simulation experiment results show that the conditional random field knowledge recognition algorithm is effective and can effectively support the analysis of automatic news Segmentation.

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The data used to support the findings of this study are available from the corresponding author upon request.

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Funding

This study did not receive any funding in any form.

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Authors and Affiliations

  1. Jilin Province Economic Management Cadre College, Changchun City, 130022, Jilin Province, China

    Chenghong Xiao

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  1. Chenghong Xiao
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CX contributed to Writing-original draft preparation, conceptualization, supervision, project administration.

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Correspondence to Chenghong Xiao.

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Xiao, C. Analysis of automatic news segmentation combining with conditional random field knowledge recognition algorithm. SIViP 18, 3867–3875 (2024). https://doi.org/10.1007/s11760-024-03048-w

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