Deep Learning-Based Web Crawler Page Rank Algorithm for Enhanced Search Relevance

Praveenkumar G D and Sadhanayaki S

International Journal of Scientific Research in Science and Technology, 2024, vol. 11, issue 2, 289-295

Abstract: A web crawler page rank algorithm employing deep learning techniques aims to revolutionize the process of indexing and ranking web pages by leveraging neural networks. By analyzing content, context, and user behavior patterns, the algorithm improves relevance, adapts dynamically to evolving web content, enhances user experience, scales efficiently, and remains robust against manipulation. This approach promises to deliver more enhance the accuracy and efficiency of web crawlers in ranking web pages.

Keywords: Web Page; Web Crawler; Feature Extraction; RNN; Page Rank Algorithm (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v11:y2024:i2:id:37

DOI: 10.32628/IJSRST52411240

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