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Internet search engines: Fluctuations in document accessibility

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  1. Internet search engines: Fluctuations in document accessibility • Wouter Mettrop CWI, Amsterdam, The Netherlands • Paul Nieuwenhuysen Vrije Universiteit Brussel, and Universitaire Instelling Antwerpen, Belgium • Hanneke Smulders Infomare Consultancy, The Netherlands Presented at Internet Librarian International 2000in London, England, March 2000

  2. WWW: growing number of WWW servers WWW

  3. Internet based information sources: how many? how much? In 2000: • about 1 billion = 1000 million unique URLs in the total Internet • about 10 terabyte (= 10 000 gigabyte) of text data

  4. Internet information retrieval systems in 2000 • Several types of systems exist to retrieve information: • Directories of selected sources categorised by subject, made by humans, mainly for browsing. • Search systems, based on databases with machine made indexes, for word-based searching! • “Meta-search” or “multi-threaded” search systems. • We have studied and compared several well-known international (and a few national) word-based Internet search engines.

  5. Internet information retrieval systems: evaluation criteria • Many aspects/criteria can be considered in the evaluation of an Internet search engine, including • coverage of documents present on WWW (studies exist) • number of elements of a document, that are indexed to make them usable for retrieval • fluctuations over time in the result sets offered by a search engine • We started to study the depth of indexing and we were soon confronted with the fluctuations in the performance that do exist.

  6. Internet information retrieval systems: our research group The following persons have been involved in the research: • Louise Beijer (Hogeschool van Amsterdam, The Netherlands) • Hans de Bruin (Unilever Research Laboratorium, Vlaardingen, The Netherlands) • Hans de Man (JdM Documentaire Informatie, Vlaardingen, The Netherlands) • Rudy Dokter (PNO Consultants, Hengelo, The Netherlands) • Marten Hofstede ( Rijksuniversiteit Leiden, The Netherlands) • Wouter Mettrop (CWI, Amsterdam, The Netherlands) • Paul Nieuwenhuysen (Vrije Universiteit Brussel, Belgium) • Eric Sieverts (Hogeschool van Amsterdam, and RUU, The Netherlands) • Hanneke Smulders (Infomare, Terneuzen, The Netherlands) • Hans van der Laan (Consultant, Leiderdorp, The Netherlands) • Ditmer Weertman (ADLIB, Utrecht, The Netherlands)

  7. Internet search engines: research on indexing functionality • assessing the indexing functionality • test document • test method • conclusions concerning indexing functionality

  8. Number of our test documents that were retrieved

  9. title tag META-tags: keywords, description and author comment tag ALT tag text/URL of a link to a document H3 tag table header text of: an internal link, a reference anchor, a link to a sound file name of a sound file (au/wav/aiff/ra) text of a link to an image name of an image file (gif or jpg; inline or linked to) name of a Java applet (with or without extension class) terms after the first 100 lines in a document (200/…/700) the URL of a document Internet search engines: elements of test document studied

  10. <HTML> <HEAD> <TITLE>Test pagina</TITLE> <META NAME="keywords" CONTENT="een, twee, drie"> <META NAME="description" CONTENT="This test page, containig a small part of the Secret Garden (by Frances Hodgson Burnett) is part of a larger site about the IRT project. vier, vijf, zes"> <META NAME="Subject" CONTENT="zeven"> <META NAME="Subject" CONTENT="acht"> <META NAME="Subject" CONTENT="negen"> <META NAME="Title” CONTENT="tien hoofdstukken uit The Secret Garden"> <META NAME="Title:Subtitle" content="elf"> Internet search engines: part of the test document source code

  11. Number of the studied document elements that were indexed

  12. Internet search engines : reachability • 14 528 queries sent to 13 search engines • 721 times unreachable • The percentage of unreachability varies from nearly 0% to nearly 15%. • The studied search engines were reachable for 95% of the queries.

  13. Search engine indexing functionality: conclusions • Not “all of the web” is indexed. • Not all of our test documents. • Not all HTML elements of our test document. • Some of the studied search engines showed changes in the indexing policy. • No relation between the number of indexed test documents or HTML elements and the size of a search engine was found during our study.

  14. Internet search engines: fluctuations - definition • A fluctuation appears when the result set of an observation - i.e. • one query or • set of queries misses documents with respect to a frame of reference - i.e. • other observations and • knowledge about Web reality

  15. Internet search engines: detecting fluctuations • Through time: comparing result sets of one observation, repeatedly performed • Observation = one query or set of queries • Frame of reference = other observations & web-knowledge • One moment: consistency of result sets • Observation = one query in set of queries • Frame of reference = other observations

  16. Internet search engines: types of fluctuations • Through time: comparing result sets of one observation repeatedly performed • “Document fluctuations” • “Indexing fluctuations” • One moment: consistency of result sets • “Element fluctuations”

  17. Document fluctuations: example 1

  18. Document fluctuations: example 2

  19. Document fluctuations: experimental results

  20. Indexing fluctuations:experimental results

  21. Element fluctuations: example

  22. Element fluctuations: experimental results

  23. Percentage of documents missed due to fluctuations

  24. Internet search engines: fluctuations - quantitative conclusions • Many element fluctuations many document and indexing fluctuations and many document elements indexed • Many document fluctuations not always many element fluctuations • Few document elements indexed few element fluctuations

  25. Fluctuations: remarks on “correctness” • Fluctuations can be seen as “correct”, if they are reflections of alterations in: • (web-) reality • then document, indexing and element fluctuations are incorrect • the indexed database of a search engine • then only element fluctuations are incorrect • Users do not care; they miss documents

  26. Fluctuations:remarks on “size” • No relation document / element fluctuations < ===== > “size” • Percentage missed documents determines (with other reducing effects, such as depth of indexing) the effective size of an engine

  27. Internet search engines: conclusions of our research • Search engines differ in depth of indexing. • Search engines show fluctuations in their result sets: • They are subject to changes in indexing policy.(“indexing fluctuations”) • They forget documents completely (“document fluctuations”) • They miss documents in their result sets (“element fluctuations”).

  28. Internet search engines: recommendations related to fluctuations • Fluctuations are “normal”; do not be surprised; do not worry. • Do not try to find a simple explanation to fully understand what happens. • Known item searchers should repeat the search • when using an engine with many element fluctuations; use other search terms; • when using an engine with many document fluctuations: repeat later. • Further research on effective size.