دانلود مقاله انگلیسی رایگان:بهبود تجسم داده های نمادین برای تشخیص الگو و کشف دانش - 2020
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دانلود مقاله انگلیسی داده های بزرگ رایگان
  • Improving symbolic data visualization for pattern recognition and knowledge discovery Improving symbolic data visualization for pattern recognition and knowledge discovery
    Improving symbolic data visualization for pattern recognition and knowledge discovery

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Improving symbolic data visualization for pattern recognition and knowledge discovery


    ترجمه فارسی عنوان مقاله:

    بهبود تجسم داده های نمادین برای تشخیص الگو و کشف دانش


    منبع:

    Sciencedirect - Elsevier - Visual Informatics, Corrected proof: doi:10:1016/j:visinf:2019:12:003


    نویسنده:

    Kadri Umbleja ∗, Manabu Ichino, Hiroyuki Yaguchi


    چکیده انگلیسی:

    This paper examines the visualization of symbolic data and considers the challenges rising from its complex structure. Symbolic data is usually aggregated from large data sets and used to hide entry specific details and to transform huge amounts of data (like big data) into analyzable quantities. It is also used to offer an overview in places where general trends are more important than individual details. Symbolic data comes in many forms like intervals, histograms, categories and modal multi-valued objects. Symbolic data can also be considered as a distribution. Currently, the de facto visualization approach for symbolic data is zoomstars which has many limitations. The biggest limitation is that the default distributions (histograms) are not supported in 2D as additional dimension is required. This paper proposes several new improvements for zoomstars which would enable it to visualize histograms in 2D by using a quantile or an equivalent interval approach. In addition, several improvements for categorical and modal variables are proposed for a clearer indication of presented categories. Recommendations for different approaches to zoomstars are offered depending on the data type and the desired goal. Furthermore, an alternative approach that allows visualizing the whole data set in comprehensive table-like graph, called shape encoding, is proposed. These visualizations and their usefulness are verified with three symbolic data sets in exploratory data mining phase to identify trends, similar objects and important features, detecting outliers and discrepancies in the data.
    Keywords: Data visualization | Symbolic data | Zoomstar | Shape encoding | Exploratory data analysis


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 9
    حجم فایل: 1135 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




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