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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

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internet search engines fluctuations in document accessibility
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

http://www.cwi.nl/cwi/projects/IRT

Presented at Internet Librarian International 2000in London, England, March 2000

internet based information sources how many how much
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
internet information retrieval systems in 2000
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.
internet information retrieval systems evaluation criteria
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.
internet information retrieval systems our research group
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)
slide7

Internet search engines: research on indexing functionality

  • assessing the indexing functionality
    • test document
    • test method
  • conclusions concerning indexing functionality
internet search engines elements of test document studied
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
internet search engines part of the test document source code
<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
internet search engines reachability
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.
search engine indexing functionality conclusions
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.
internet search engines fluctuations definition
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
internet search engines detecting fluctuations
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
internet search engines t ypes of fluctuations
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”
internet search engines fluctuations quantitative conclusions
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
fluctuations remarks on correctness
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
fluctuations remarks on size
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
internet search engines conclusions of our research
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”).
internet search engines recommendations related to fluctuations
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.