The paper introduces PageRank, a method for objectively ranking web pages based on their importance, which is determined by the link structure of the web. PageRank aims to address the subjective nature of web page importance and the challenges posed by the vast and heterogeneous nature of the World Wide Web. The authors compare PageRank to an idealized random web surfer and demonstrate efficient computation methods for large numbers of pages. They also explore applications of PageRank in search engines, user navigation, and traffic estimation. The paper discusses the diversity of web pages and the limitations of simple citation counting methods, highlighting the need for a more sophisticated approach. PageRank is defined mathematically and implemented in a crawling and indexing system, with experiments showing its effectiveness in various scenarios. The paper concludes by discussing the benefits of PageRank in improving search results and its potential for personalized and traffic estimation applications.The paper introduces PageRank, a method for objectively ranking web pages based on their importance, which is determined by the link structure of the web. PageRank aims to address the subjective nature of web page importance and the challenges posed by the vast and heterogeneous nature of the World Wide Web. The authors compare PageRank to an idealized random web surfer and demonstrate efficient computation methods for large numbers of pages. They also explore applications of PageRank in search engines, user navigation, and traffic estimation. The paper discusses the diversity of web pages and the limitations of simple citation counting methods, highlighting the need for a more sophisticated approach. PageRank is defined mathematically and implemented in a crawling and indexing system, with experiments showing its effectiveness in various scenarios. The paper concludes by discussing the benefits of PageRank in improving search results and its potential for personalized and traffic estimation applications.