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Visual Trend Analysis with Digital Libraries

Nazemi, Kawa and Retz, Reimond and Burkhardt, Dirk and Kuijper, Arjan and Kohlhammer, Jörn and Fellner, Dieter W. (2015):
Visual Trend Analysis with Digital Libraries.
ACM, New York, In: i-KNOW 2015, Graz, 21. und 22. Oktober 2015, In: ACM International Conference Proceedings Series; 1098, DOI: 10.1145/2809563.2809569, [Conference or Workshop Item]

Abstract

The early awareness of new technologies and upcoming trends is essential for making strategic decisions in enterprises and research. Trends may signal that technologies or related topics might be of great interest in the future or obsolete for future directions. The identification of such trends premises analytical skills that can be supported through trend mining and visual analytics. Thus the earliest trends or signals commonly appear in science, the investigation of digital libraries in this context is inevitable. However, digital libraries do not provide sufficient information for analyzing trends. It is necessary to integrate data, extract information from the integrated data and provide effective interactive visual analysis tools. We introduce in this paper a model that investigates all stages from data integration to interactive visualization for identifying trends and analyzing the market situation through our visual trend analysis environment. Our approach improves the visual analysis of trends by investigating the entire transformation steps from raw and structured data to visual representations.

Item Type: Conference or Workshop Item
Erschienen: 2015
Creators: Nazemi, Kawa and Retz, Reimond and Burkhardt, Dirk and Kuijper, Arjan and Kohlhammer, Jörn and Fellner, Dieter W.
Title: Visual Trend Analysis with Digital Libraries
Language: English
Abstract:

The early awareness of new technologies and upcoming trends is essential for making strategic decisions in enterprises and research. Trends may signal that technologies or related topics might be of great interest in the future or obsolete for future directions. The identification of such trends premises analytical skills that can be supported through trend mining and visual analytics. Thus the earliest trends or signals commonly appear in science, the investigation of digital libraries in this context is inevitable. However, digital libraries do not provide sufficient information for analyzing trends. It is necessary to integrate data, extract information from the integrated data and provide effective interactive visual analysis tools. We introduce in this paper a model that investigates all stages from data integration to interactive visualization for identifying trends and analyzing the market situation through our visual trend analysis environment. Our approach improves the visual analysis of trends by investigating the entire transformation steps from raw and structured data to visual representations.

Series Name: ACM International Conference Proceedings Series; 1098
Publisher: ACM, New York
Uncontrolled Keywords: Business Field: Visual decision support, Research Area: Human computer interaction (HCI), Forschungsgruppe Semantic Models, Immersive Systems (SMIS), Visual analytics, Information visualization, Data integration, Data mining, Trend analysis, Information extraction
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: i-KNOW 2015
Event Location: Graz
Event Dates: 21. und 22. Oktober 2015
Date Deposited: 08 May 2019 08:07
DOI: 10.1145/2809563.2809569
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