Search Results - "H.2.8 Database applications. Data mining"

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  1. 1

    iVisClustering: An Interactive Visual Document Clustering via Topic Modeling by Lee, Hanseung, Kihm, Jaeyeon, Choo, Jaegul, Stasko, John, Park, Haesun

    ISSN: 0167-7055, 1467-8659
    Published: Oxford, UK Blackwell Publishing Ltd 01.06.2012
    Published in Computer graphics forum (01.06.2012)
    “…Clustering plays an important role in many large‐scale data analyses providing users with an overall understanding of their data. Nonetheless, clustering is…”
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    Journal Article
  2. 2

    Subspace search and visualization to make sense of alternative clusterings in high-dimensional data by Tatu, A., Maas, F., Farber, I., Bertini, E., Schreck, T., Seidl, T., Keim, D.

    ISBN: 1467347523, 9781467347525
    Published: IEEE 01.01.2012
    “…In explorative data analysis, the data under consideration often resides in a high-dimensional (HD) data space. Currently many methods are available to analyze…”
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    Conference Proceeding
  3. 3

    Using random projections to identify class-separating variables in high-dimensional spaces by Anand, A., Wilkinson, L., Tuan Nhon Dang

    ISBN: 1467300152, 9781467300155
    Published: IEEE 01.10.2011
    “…Projection Pursuit has been an effective method for finding interesting low-dimensional (usually 2D) projections in multidimensional spaces. Unfortunately,…”
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    Conference Proceeding
  4. 4

    Visual analytics for detecting behaviour patterns in geo-temporal data by Hundt, Michael, Siirak, Natascha M., Wildnei, Manuel

    Published: IEEE 01.10.2014
    “…Today raw data get more complex and are obtained from different sources. In this paper, the data sources evaluated are GPS tracks of thirty five cards and…”
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    Conference Proceeding
  5. 5

    Visual Exploration of Spatio-temporal Relationships for Scientific Data by Mehta, S., Parthasarathy, S., Machiraju, R.

    ISBN: 1424405912, 9781424405916
    Published: IEEE 01.10.2006
    “…Spatio-temporal relationships among features extracted from temporally-varying scientific datasets can provide useful information about the evolution of an…”
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    Conference Proceeding