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<p>In the contemporary integrated media environment, the innovation of enterprise short video operation and management, as well as the strategic utilization of modern network technologies, are pivotal in amplifying an enterprise’s influence among users on burgeoning integrated media platforms. This study delves into refining the existing recommendation algorithms, which are crucial for enhancing user engagement and retention rates in enterprise short video services. By integrating the Vulture Search Algorithm to optimize the Fuzzy C-Means user clustering technique and leveraging user profiles developed from questionnaire surveys, this research pioneers a novel approach for tailoring the short video recommendation processes. The enhanced algorithm effectively addresses research needs aligned with user pReferencesand enhances the Fuzzy C-Means method. The application of this refined recommendation algorithm demonstrated significant improvements in user stickiness, driven by the recommendations’ accuracy, engagement, enjoyment, and novelty. Factor analysis revealed that these attributes account for 89.553% of the total variance, which highlights their significant impact on user engagement. Consequently, enterprises seeking to innovate their short video operations within the integrated media landscape must prioritize optimizing video recommendation systems to foster user attachment and satisfaction.</p>
</abstract>

In the contemporary integrated media environment, the innovation of enterprise short video operation and management, as well as the strategic utilization of modern network technologies, are pivotal in amplifying an enterprise’s influence among users on burgeoning integrated media platforms. This study delves into refining the existing recommendation algorithms, which are crucial for enhancing user engagement and retention rates in enterprise short video services. By integrating the Vulture Search Algorithm to optimize the Fuzzy C-Means user clustering technique and leveraging user profiles developed from questionnaire surveys, this research pioneers a novel approach for tailoring the short video recommendation processes. The enhanced algorithm effectively addresses research needs aligned with user pReferencesand enhances the Fuzzy C-Means method. The application of this refined recommendation algorithm demonstrated significant improvements in user stickiness, driven by the recommendations’ accuracy, engagement, enjoyment, and novelty. Factor analysis revealed that these attributes account for 89.553% of the total variance, which highlights their significant impact on user engagement. Consequently, enterprises seeking to innovate their short video operations within the integrated media landscape must prioritize optimizing video recommendation systems to foster user attachment and satisfaction.

Innovation and Practice of Enterprise Short Video Operation and Management Mode in Melting Media Environment

Degree of Doctor of Business Administration, Pathumthani University

DOCTOR OF PHILOSOPHY (Economics), Universiti Sains Malaysia

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In the contemporary integrated media environment, the innovation of enterprise short video operation and management, as well as the strategic utilization of...

Innovation and Practice of Enterprise Short Video Operation and Management Mode in Melting Media Environment

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 03. Apr. 2024

Akzeptiert: 01. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2019

Schlüsselwörter
Short video operation, Vulture search algorithm, User portrait, User stickiness

© 2024 Yueji Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Innovation and Practice of Enterprise Short Video Operation and Management Mode in Melting Media Environment

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 03. Apr. 2024

Akzeptiert: 01. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2019

SchlüsselwörterShort video operation, Vulture search algorithm, User portrait, User stickiness

© 2024 Yueji Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Short video operation, Vulture search algorithm, User portrait, User stickiness