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Enhancing Web Search Strategies: Beyond SEO Basics

This module explores advanced topics in web search including authority estimation, computational advertizing, adversarial IR, result filtering, and Internet Archive overview. Learn how to influence rankings, optimize content, and address challenges in the evolving search landscape. Dive into indexing, user-controlled suppression, and temporal variations in search behaviors.

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Enhancing Web Search Strategies: Beyond SEO Basics

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  1. Web Search Module 6 INST 734 Doug Oard

  2. Agenda • The Web • Crawling • Web search

  3. Query Statistics Pass, et al., “A Picture of Search,” 2007

  4. Periodic Daily Variation Pass, et al., “A Picture of Search,” 2007

  5. Pass, et al., “A Picture of Search,” 2007

  6. Pass, et al., “A Picture of Search,” 2007

  7. BurstinessQuery: Earthquake http://www.google.com/trends/

  8. 28% of Queries are Reformulations Pass, et al., “A Picture of Search,” 2007

  9. Indexing Anchor Text • A type of “document expansion” • Terms near links describe content of the target • Works even when you can’t index content • Image retrieval, uncrawled links, …

  10. Estimating Authority from Links Hub Authority Authority

  11. Aggregated Search

  12. Computational Advertizing • Variant of a search problem • Jointly optimize relevance and revenue • Triangulating evidence • Queries • Clicks • Page visits • Obtaining evidence • Advertising networks • Online auctions

  13. Adversarial IR • Search is user-controlled suppression • Everything is known to the search system • Goal: avoid showing things the user doesn’t want • Other stakeholders have different goals • Authors risk little by wasting your time • Marketers may hope for serendipitous interest

  14. Influencing the Ranking • Search Engine Optimization (SEO) • Alter your content to better match user queries • Create partnerships to drive traffic (and links) • Index Spam • Create bogus user-assigned metadata • Add invisible text (font in background color, …) • Cloaking • Link exchange

  15. Result Filtering (“Safe Search”) • Source analysis • Whitelists, blacklists • Content analysis • Text, image analysis, … • Contextual analysis • Links, user activity, …

  16. Internet Archive

  17. Web Search Summary • Different content • Links • User-generated • Crawling • Different searches • Different goals (transactions, advertising, …) • Temporal variations and burstiness • Different interaction designs

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