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Searching the Web II

Searching the Web II. The Web. Why is it important: “Free” ubiquitous information resource Broad coverage of topics and perspectives Becoming dominant information collection Growth and jobs Web access methods Search (e.g. Google) Directories (e.g. Yahoo!) Other …. Web Characteristics.

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Searching the Web II

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  1. Searching the Web II

  2. The Web • Why is it important: • “Free” ubiquitous information resource • Broad coverage of topics and perspectives • Becoming dominant information collection • Growth and jobs • Web access methods Search (e.g. Google) Directories (e.g. Yahoo!) Other …

  3. Web Characteristics • Distributed data • High volatility • Large volume • Unstructured data • Quality of data • Heterogeneous data

  4. Web Tasks • Precision is the key • Goal: first 10-100 results should satisfy user • Requires ranking that matches user’s need • Recall is not important • Completeness of index is not important • Comprehensive crawling is not important

  5. Browsing • Web directories • Human-organized taxonomies of Web sites • Small portion (< than 1%) of Web pages • Remember that recall (completeness) is not important • Directories point to logical web sites rather than pages • Directory search returns both categories and sites • People generally browse rather than search once they identify categories of interest

  6. Metasearch • Search a number of search engines • Advantages • Do not build their own crawler and index • Cover more of the Web than any of their component search engines • Difficulties • Need to translate query to each engine query language • Need to merge results into a meaningful ranking

  7. Metasearch II • Merging Results • Voting scheme based on component search engines • No model of component ranking schemes needed • Model-based merging • Need understanding of relative ranking, potentially by query type • Why they are not used for the Web • Bias towards coverage (e.g. recall), which is not important for most Web queries • Merging results is largely ad-hoc, so search engines tend to do better • Big application: the Dark Web

  8. Using Structure in Search • Languages to search content and structure • Query languages over labeled graphs • PHIQL: Used in Microplis and PHIDIAS hypertext systems • Web-oriented: W3QL, WebSQL, WebLog, WQL

  9. Using Structure in Search • Other use of structure in search • Relevant pages have neighbors that also tend to be relevant • Search approaches that collect (and filter) neighbors to returned pages

  10. Web Query Characteristics • Few terms and operators • Average 2.35 terms per query • 25% of queries have a single term • Average 0.41 operators per query • Queries get repeated • Average 3.97 instances of each query • This is very uneven (e.g. “Britney Spears” vs. “Frank Shipman”) • Query sessions are short • Average 2.02 queries per session • Average of 1.39 pages of results examined • Data from 1998 study • How different today?

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