EuroVA16

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https://diglib.eg.org/handle/10.2312/15279

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Browsing EuroVA16 by Subject "I.3.3 [Computer Graphics]"

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    An Art-based Approach to Visual Analytics
    (The Eurographics Association, 2016) Sehgal, Gunjan; Sharma, Geetika; Natalia Andrienko and Michael Sedlmair
    In this paper, we propose an art-based approach to visual analytics.We argue that while artistic data visualizations have mainly been designed to communicate the artist's message, certain artistic styles can be very effective in exploratory data analysis as well and data visualizations can benefit from more than just the aesthetics inspired by art. We use the ancient Warli style of tribal paintings, found in western India to demonstrate the use of artistic styles for visual analytics over open data provided by the Indian government.
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    Patent Retrieval: A Multi-Modal Visual Analytics Approach
    (The Eurographics Association, 2016) Seebacher, Daniel; Stein, Manuel; Janetzko, Halldór; Keim, Daniel A.; Natalia Andrienko and Michael Sedlmair
    Claiming intellectual property for an invention by patents is a common way to protect ideas and technological advancements. However, patents allow only the protection of new ideas. Assessing the novelty of filed patent applications is a very time-consuming, yet crucial manual task. Current patent retrieval systems do not make use of all available data and do not explain the similarity between patents. We support patent officials by an enhanced Visual Analytics multi-modal patent retrieval system. Including various similarity measurements and incorporating user feedback, we are able to achieve significantly better query results than state-of-the-art methods.