Media Content Mining Based on Artificial Intelligence and Network Interaction

Kang, Kai; Wang, Zhixue; Zhang, Hongwu

doi:10.1155/2022/6705986

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…By training a large amount of video data, the model is able to learn the features and laws of the video content and then generate new video content. In addition, AIGC technology also combines computer vision technology, which can identify, analyze, and process the images in the video so as to achieve more intelligent video editing [9][10].…”

Section: Introductionmentioning

confidence: 99%

Principles of AIGC technology and its application in new media micro-video creation

2024

Applied Mathematics and Nonlinear Sciences

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AIGC, as a new generation of intelligent generation technology, provides new ideas for the progress and development of the new media field. This study constructs a communication model for new media micro-video creation based on the information communication model, analyzing the communication and development of new media micro-video creation. Combining the application characteristics of AIGC technology in new media micro-video creation and the needs of new media micro-video creation, it proposes the information hiding improvement method based on the GAN model and diffusion model. It constructs the AIGC optimization system based on new media micro-video creation. The model’s application effect in new media micro-video creation is explored after it passes the performance test. The results show that the average scores of all the indicators of the sense of using experience are above 3.5, the overall average score of micro-video creation is 4.12, and the peak traffic and cumulative traffic of the works created by utilizing this method have been improved by 17,000 and 1,910,000, respectively. The efficiency and quality of micro-video creation can be enhanced by using this study as a feasible reference.

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Section: Introductionmentioning

confidence: 99%

Principles of AIGC technology and its application in new media micro-video creation

2024

Applied Mathematics and Nonlinear Sciences

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“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”

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confidence: 99%

Retracted: Media Content Mining Based on Artificial Intelligence and Network Interaction

2023

Mobile Information Systems

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Text Mining Techniques for Linguistic Characterization of Jewish Literature - An Example from Philip Roth’s Goodbye, Columbus

Zhang

2024

Applied Mathematics and Nonlinear Sciences

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Text mining technology holds considerable potential for augmenting research in the humanities, offering a novel approach to overcome the limitations inherent in traditional introspective methodologies and introducing innovative perspectives for literary analysis. This study explores the application of text mining within the humanities and social sciences, employing the Term Frequency-Inverse Document Frequency (TF-IDF) method for the feature vector representation of textual information. It constructs a linguistic feature analysis model using three computational techniques: support vector machine, logistic regression, and the naive Bayesian model. Philip Roth’s “Goodbye, Columbus” serves as the focal point of this research. The study involves preprocessing the text corpus and subsequently comparing the performance indices of the three linguistic feature analysis models to delve deeper into the relevance of syntactic and semantic feature analysis. The evaluation criteria used to delineate the linguistic characteristics of Jewish literature are identified and employed to conclude. Among the models tested, the support vector machine model demonstrates superior performance, evidenced by its higher accuracy (0.839), precision (0.866), and F-value (0.874) relative to the other models. The analysis identifies the most influential features for capturing the linguistic essence of Jewish literature as the proportion of dialogue, sentence disjunction, average word length, and word disjunction. The selected sample of Jewish literature exhibited notable characteristics, including dialogue richness (0.369), sentence rhythm (0.234), and linguistic richness (0.266). The findings affirm that the text-mining approach utilized in this study significantly enhances the linguistic characterization of Jewish literature. This method proves effective in assisting the linguistic analysis and research of Jewish literary works, thereby reinforcing the value of integrating advanced computational techniques in humanities research.

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Media Content Mining Based on Artificial Intelligence and Network Interaction

Cited by 3 publications

References 21 publications

Principles of AIGC technology and its application in new media micro-video creation

Principles of AIGC technology and its application in new media micro-video creation

Retracted: Media Content Mining Based on Artificial Intelligence and Network Interaction

Text Mining Techniques for Linguistic Characterization of Jewish Literature - An Example from Philip Roth’s Goodbye, Columbus

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