The quality of search engines is influenced by various factors,and in most cases,it depends on the ranking algorithm,so the ranking algorithm is crucial for search engines.Firstly,leveraging the sparsity-promoting advantage of the FTRL algorithm,the features impacting the ranking algorithm were selected.Subsequently,a search engine ranking algorithm based on the fusion of multiple features was proposed to optimize the ranking performance of the search engine.The experimental results demonstrate that the algorithm proposed can effectively enhance the accuracy of the search engine ranking algorithm,outperforming traditional ranking algorithms.
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