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Modeling Web Crawling Process with Zipf’s Law for Web Graph Understanding

This paper explores the use of Zipf’s law to model web crawling processes and compares the results to existing web graph models. It discusses the relationship between web crawls and web graphs, focusing on algorithms like PageRank and HITS. The study examines sociological hypotheses commonly used to model web graphs, emphasizing the unique aspects of web crawls as opposed to web graphs. The evaluation criteria employed mirror those observed in graphs following Zipf’s law. The paper is closely linked to social networks, small world phenomenon, A/H, and page ranks, providing insights into the study of crawlers.

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Modeling Web Crawling Process with Zipf’s Law for Web Graph Understanding

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Presentation Transcript

  1. Problem Addressed • Attempts to prove that Web Crawl is random & biased image of Web Graph and does not assert properties of Web Graph • Understanding the Hyperlink structure has allowed the design of Algorithms like PageRank, HITS etc

  2. Approach • Generally authors use sociological hypothesis to model the web graphs & compare the graphs with existing crawls • This paper attempts to model the web crawling process using only Zipf’s law but arrive at results comparable to existing web graph models.

  3. Criticism • Uses Zipf’s law to model the crawling process, but also uses Zipf’s law in evaluation • Most of the evaluation criteria used are commonly observed in graphs following Zipf’s law • Concludes that Web Crawls are different from Web Graphs without proving it

  4. Relation to Course • Closely related to Social Networks as it discusses Zipf’s law, Small World Phenomenon, A/H, Page Ranks etc. • Related to the study of Crawlers

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