Please send your PIN to firstname.lastname@example.org if you are interested in presenting in this session.
Web-based platforms have now become one of the most efficient ways for information dissemination due to the rapid development of the World Wide Web and cyberinfrastructure in recent decades. For instance, the remarkable success of online social media sites marks a shift in the way people connect and share information. Integrated with innovative data mining methods, researchers are able to uncover the potential disciplines and mechanisms instead of simply displaying the original data. Specifically with large volumes of spatiotemporal data available in different application areas including business intelligence, human mobility, transportation planning and climate change, geographers are able to explore the underlying research questions and obtain comprehensive understanding about the spatiotemporal processes. This organized paper session will focus on the development of innovative data discovery and mining methods based on web platforms and the applications of web-based technologies in a variety of areas. Topics of interest for this session include, but are not limited to:
1) Innovative Earth science data discovery algorithms such as ranking and recommendation systems
2) Knowledge discovery from free text with natural language processing
3) Design and implementation of Web-based data discovery infrastructure
4) Discussions on current status, problems and future development of data discovery
5) Applications of web-based visualizations in climate, oceanography, urban planning, environmental issues, etc.
|Presenter||Jingchao Yang*, George Mason University, Private Cloud Platform In Improving The Performance of GIS Analysis||20||5:20 PM|
|Presenter||Alexander Hohl*, University of North Carolina - Charlotte, Space-Time GIS Using Ripley’s K Function||20||5:40 PM|
|Presenter||Lauren Bennett*, Esri, An applied framework for statistical analysis of spatiotemporal data||20||6:00 PM|
|Presenter||Sooyeon Yi*, University of California - Berkeley, Projecting future inland flooding susceptibility due to climate change in California using machine learning Yang Ju, University of California - Berkeley, Projecting future inland flooding susceptibility due to climate change in California using machine learning Yiyi He, University of California - Berkeley, Projecting future inland flooding susceptibility due to climate change in California using machine learning||20||6:20 PM|
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