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Title: Title: AID, an Associative Interactive Dictionary for Onlin


1
Controlled Vocabularies in Searching
Tamas Doszkocs, Ph.D.Computer
Scientistdoszkocs_at_nlm.nih.gov
2
Controlled Vocabularies
  • Definition
  • Purpose and Role
  • A Brief History
  • Who is in Control?
  • Spell Checkers
  • Folksonomies
  • Tagging
  • Search Focus
  • Search refinement
  • Web X.Y

3
Related Topics(that we wont talk about)
4
Definition and Purpose
  • Controlled vocabulary is a list of terms that
    have been enumerated explicitly.
  • In Library and Information Science Controlled
    vocabulary is a carefully selected list of words
    and phrases, which are used to tag units of
    information so that they may be more easily
    retrieved by a search. The terms are chosen and
    organized by trained professionals (including
    librarians and information scientists) who
    possess expertise in the subject area. Controlled
    vocabulary terms can accurately describe what a
    given document is actually about, even if the
    terms themselves do not occur within the
    document's text. Fully developed controlled
    vocabulary systems, such as the Library of
    Congress Subject Headings, are often published in
    a reference work that is called a thesaurus.
    Controlled vocabularies form part of a larger
    universe of nomenclatural approaches to data
    classification called metadata. (Wikipedia)

5
More Information
  • Bridging the gap between languages used by
    authors, search systems and users
  • http//sky.fit.qut.edu.au/middletm/cont_voc.html
  • http//www.controlledvocabulary.com/
  • http//php.iupui.edu/kcmcreyn/su03/control.html
  • http//www.hsl.creighton.edu/hsl/Searching/c-vocab
    1.html
  • http//www.dlese.org/Metadata/vocabularies/term_ex
    pln.htm

6
A Brief History
  • The 1970s and 1980s bloody battles and
    casualties
  • Controlled vocabularies vs. natural language
  • Command languages vs. free-form queries
  • CVs vs. abstracts vs. full text
  • Librarians vs. end users
  • The 1990s and the Web natural language for the
    masses
  • The 21st Century the best of both worlds

7
Vocabulary Control for Information Retrieval, 1972
  • by F. Wilfrid Lancaster
  •  
  • About this title Contents- Why Vocabulary
    Control? Pre-coordinate Post-coordinate
    Systems Vocabulary Structure Display
    Gathering the Raw Material Standards
    Guidelines Organization of Terms The
    Hierarchical Relationship Organization of
    Terms The Associative Relationship Terms Form
    Compounding The Entry Vocabulary Homography
    Scope Notes Thesaurus Display Vocabulary
    Growth Updating The Role of the Computer
    Identifiers Checklists The Influences of
    Vocabulary on the Performance of a Retrieval
    System Evaluation of Thesauri
    Natural-language Searching the Post-controlled
    Vocabulary Hybrid Systems Compatibility
    Convertibility Multilingual Aspects Automatic
    Approaches to Thesaurus Construction Some
    Cost-effectiveness Aspects of Vocabulary Control
    Bibliography Index. "The publisher's
    announcement claims that the original edition is
    an information science classic that has emerged
    as the 'bible' of indexing retrieval
    vocabularies, (is the) first definitive
    monograph devoted exclusively to controlled
    vocabularies in information retrieval. ..

8
An Associative Interactive Dictionary for Online
Searching, 1978
  • Title AID, an Associative Interactive
    Dictionary for Online Searching.
  • Authors Doszkocs, Tamas E.
  • Descriptors
  • Dictionaries - Information Retrieval - Online
    Systems - Search Strategies -  Tables (Data)
    - Word Frequency
  • Source On-Line Review, v2 n2 p163-73 Jun 1978,
    Jun78
  • AID meta-searched MEDLINE, TOXLINE and the
    Hepatitis Databank and displayed result clusters
    of keywords and MeSH headings

9
CITE, 1979
  • Doszkocs T. E., Rapp B. A. Searching Medline in
    English A prototype user interface with natural
    language query, ranked output and relevance
    feedback. Proc. ASlS Annu. Meet. Vol 16 pp
    131-137 1979.
  • Automatic suggestion of Medical Subject Headings
  • Used as NLMs OPAC 1979-1984

10
WebLine, 1994
  • The first Web interface to an online retrieval
    system
  • Associative Concept Navigation in MEDLINE and
    other NLM Databases via a Mosaic - Forms - WWW
    Interface Combining Natural Language Processing,
    Expert Systems and (un)Conventional Information
    Retrieval Techniques Tamas E. Doszkocs, Seth B.
    Widoff, Bruno M. Vasta National Library of
    Medicine in Proceedings of the Second World
    Wide Web Conference , Chicago 1994
  • http//www.ncsa.uiuc.edu/SDG/IT94/Proceedings/Sear
    ching/doszkocs/doszkocs.html
  • see also WebCrawler (Brian Pinkerton)
  • The Open Web and the Hidden Web

11
Jerrys Guide to the Web, 1994
  • Jerry Yang and David Filos Yahoo! 1995
  • a directory of web sites, organized in a
    hierarchy of subject descriptors
  • Librarians at Yahoo
  • Surfing is to Yahoo! what the Dewey Decimal
    System is to libraries. In other words, Surfing
    is the categorization of websites. It also
    happens to be how Yahoo! began. Today our Surfing
    team continues its passion for finding,
    evaluating, and organizing information on the
    Internet. They have a voracious appetite for
    learning about new topics. They are curious
    individuals who are skilled at intuitively and
    efficiently analyzing and classifying diverse,
    unstructured pieces of information across the
    Yahoo! network. Surfers are critical to the
    relevance and intuitive nature of information
    presented on Yahoo!. http//careers.yahoo.com/job_
    descriptions.html

12
The Remains of the Yahoo Directory
13
(No Transcript)
14
(No Transcript)
15
Open Directory Project
16
(No Transcript)
17
Transparent Query Mapping to Controlled
Vocabulary Terms
18
Spell Checking as a Controlled Vocabulary
Application
19
Correct spelling, correct results
20
Folksonomies and Social Tagging
21
Tagging in Flickr
22
Query Refinement with Phrases
23
Query Refinement with Subject Headings
24
Focusing in Search Results with Topical Clusters
25
Clustering of Search Results with Phrases
26
Clustering and Search Refinement with Natural
Language and Controlled Vocabularies
27
Clustering with Multiple Criteria
28
Analyzing Search Results
29
Visualizing Search results
30
Multi-faceted Clustering in an OPAC
31
AllPlus Web 2.0 Content Mashup
32
AllPlus Dynamic Cluster Visualization
33
Controlled Vocabularies in Searching
Tamas Doszkocs, Ph.D.Computer
Scientistdoszkocs_at_nlm.nih.gov
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