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Content based visual mining of document collections using ontologies
University of São Paulo, Brazil.
University of São Paulo, Brazil.ORCID iD: 0000-0002-2901-935X
University of São Paulo, Brazil.
University of São Paulo, Brazil.
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2009 (English)In: II Workshop on Web and Text Intelligence (WTI) 2009, 2009Conference paper, Published paper (Refereed)
Abstract [en]

Document collections are important data sets in many applications. It has been shown that content based visual mappings of documents can be done effectively through projection and point placement strategies. An important step in this process is the creation of a vector space model, in which terms selected from the text and weighted are used as attributes for the vector space. That step in many cases impairs the quality of the projection due to the existence, in the data set, of many terms that are frequent but do not represent important concepts in the user's particular context. This paper proposes and evaluates the use of ontologies for content based visual analysis of textual data sets as a means to improve the displays for the analysis of the collection. The results show that when the ontology effectively represents the data domain it increases quality of maps.

Place, publisher, year, edition, pages
2009.
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-73257OAI: oai:DiVA.org:lnu-73257DiVA, id: diva2:1199801
Conference
II Workshop on Web and Text Intelligence (WTI) 2009
Available from: 2018-04-22 Created: 2018-04-22 Last updated: 2018-08-10Bibliographically approved

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Martins, Rafael Messias

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf