Research on optimizing advertising conversion rates on short video platforms based on an improved full-space task model

Advertising has become a critical monetization strategy with the rapid development of short video platforms, However, optimizing advertising conversion rates remains a challenge due to the complex user behaviors dynamic content interactions on these platforms. That proposes an improved full-space task model enhance the accuracy of advertisement targeting conversion rate optimization. By integrating deep learning algorithms behavioral data mining multi-dimensional user profiling, the model refines ad placement strategies improves engagement metrics. Experimental results based on realworld short video platform datasets demonstrate that the proposed model outperforms traditional methods in terms of conversion efficiency user retention cost-effectiveness. That research provides valuable insights advertisers platform operators seeking maximize the impact of their ad campaigns.