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Using content analysis to support the noise detechtion and visualization of shared workspaces

dc.contributor.authorPrinz, Wolfgangde_DE
dc.contributor.authorZaman, Baberde_DE
dc.contributor.editorStary, Christiande_DE
dc.date.accessioned2017-11-22T14:41:57Z
dc.date.available2017-11-22T14:41:57Z
dc.date.issued2005
dc.description.abstractShared workspace systems provide virtual places for self-organized and semi-structured cooperation between local and distributed users. These systems are adopted by a large community over the past years and the volume of information managed by these systems is expanding rapidly. A problem that occurs frequently using these systems is the missing user support for the workspace organization and assistance for finding the right place for storing new contributions. This often results in weakly organized workspaces making it difficult to find documents. Current systems do not provide support for the identification of the homogeneity of the workspace content. Thus, support to find noisy documents and providing appropriate alternative locations is missing. This paper presents a solution that helps to detect such noise in workspaces and to provide alternative suggestions for the workspace organization. The visualization of the inter-folder similarity in workspaces helps users to find redundant folders and to reorganize the workspace hierarchy. The support for finding similar documents to a given document helps users to find related documents easily.de_DE
dc.identifier.isbn3-486-57805-7
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/6988
dc.language.isoen
dc.publisherOldenbourg Verlagde_DE
dc.relation.ispartofMensch und Computer 2005: Kunst und Wissenschaft - Grenzüberschreitung der interaktiven Artde_DE
dc.titleUsing content analysis to support the noise detechtion and visualization of shared workspacesde_DE
dc.typeText/Conference Paperde_DE
gi.citation.endPage180
gi.citation.publisherPlaceMünchende_DE
gi.citation.startPage171
gi.conference.sessiontitleExplorierung von Informationsräumende_DE
gi.document.qualitydigidocen_US

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