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Differentiate between Page Rank & HITS algorithm.

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Criteria PageRank HITS (Hyperlink-Induced Topic Search)
Purpose Measures the importance of web pages based on link structure. Identifies authority and hub pages in a network.
Algorithm Type Link Analysis Link Analysis
Developed by Larry Page and Sergey Brin (Google) Jon Kleinberg (Cornell University)
Key Idea Pages with more incoming links are more important. Authority pages link to many hub pages, and hub pages link to many authority pages.
Computation Method Iterative algorithm that assigns a PageRank score to each page. Iterative algorithm that computes two scores: authority and hub scores.
Scoring Metric PageRank score for each page. Authority and hub scores for each page.
Output Rank pages by importance. Identify authority and hub pages.
Dangling Nodes Handling Typically handled by redistributing their PageRank. Often ignored in HITS.
Convergence Usually converges slowly. Can converge faster than PageRank.
Query-Dependent PageRank scores are query-independent. HITS can be adapted for query-specific searches.
Use in Search Engines Used by Google and many other search engines. Less commonly used in modern search engines.
Vulnerability to Manipulation Susceptible to link spam and link manipulation. Less susceptible to manipulation, as it focuses on the structure of the network.

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