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A Hybrid Page Ranking Algorithm Based on User Behavior

Search engine, one of the most important applications in our lives, is dependent on page ranking algorithm. User search experience is directly affected by the quality of the page ranking algorithm, and poor ranking leads to users spending much more time to find their desired webpage from the search results. This study, on the basis of the Weighted PageRank algorithm, proposes a new algorithm, the Topic Weighted PageRank algorithm, that considers topic relevance between webpage content and users' search queries, and ensures ranking results are strongly correlated to user needs. Subsequently, this study improved the Topic Weighted PageRank algorithm in many aspects after considering factors such as the popularity of webpages, user preference for websites, and user preference. Finally, indicators of page ranking algorithm effectiveness were defined, and experiments were conducted to verify the effectiveness of the page ranking method proposed in this study. The results show that the proposed page ranking method performs better in various indicators than many of page ranking algorithms declared in recent years.