Process Support and Visual Adaptation to Assist Visual Trend Analytics in Managing Transportation Innovations
In the domain of mobility and logistics, a variety of new technologies and business ideas are arising. Beside technologies that aim on ecologically and economic transportation, such as electric engines, there are also fundamental different approaches like central packaging stations or deliveries via drones. Yet, there is a growing need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance. Commonly adaptive systems investigate only the users’ behavior, while a process-related supports could assist to solve an analytical task more efficient and effective. In this article an approach that enables non-experts to perform visual trend analysis through an advanced process support based on process mining is described. This allow us to calculate a process model based on events, which is the baseline for process support feature calculation. These features and the process model enable to assist non-expert users in complex analytical tasks.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9783030396879
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Supplemental Notes:
- © Springer Nature Switzerland AG 2020. The contents of this paper reflect the views of the authors and do not necessarily reflect the official views or policies of the Transportation Research Board or the National Academy of Sciences.
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Corporate Authors:
Springer International Publishing
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Authors:
- Burkhardt, Dirk
- Nazemi, Kawa
- Ginters, Egils
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Conference:
- ICTE in Transportation and Logistics (ICTE 2019)
- Date: 2019-9-10 to 2019-9-13
- Publication Date: 2020-1
Language
- English
Media Info
- Media Type: Web
- Edition: 1
- Features: References;
- Pagination: pp 319-327
- Monograph Title: ICTE in Transportation and Logistics 2019
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Serial:
- Lecture Notes in Intelligent Transportation and Infrastructure
- Publisher: Springer Cham
- ISSN: 2523-3440
- EISSN: 2523-3459
- Serial URL: https://www.springer.com/series/15991
Subject/Index Terms
- TRT Terms: Adaptive control; Logistics; Mobility; Technological innovations; Trend (Statistics); Visualization
- Subject Areas: Highways; Planning and Forecasting;
Filing Info
- Accession Number: 01874349
- Record Type: Publication
- ISBN: 9783030396879
- Files: TRIS
- Created Date: Feb 23 2023 9:31AM