Mining volunteered geographic information for predictive energy data analytics

Mining volunteered geographic information for predictive energy data analytics

Abstract Background Users create serious amounts of Volunteered Geographic Information (VGI) in Online platforms like OpenStreetMap or in real estate portals. Harvesting such data with the help of business analytics and machine learning methods yield promising opportunities for firms to create addit...

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Bibliographic Details
Main Author: Konstantin Hopf
Format: Article
Language:English
Published: SpringerOpen 2018-07-01
Series:Energy Informatics
Subjects:
Volunteered geographic information
Energy data analytics
Energy retail
Predictive analytics
Machine learning
Household classification
Online Access:http://link.springer.com/article/10.1186/s42162-018-0009-3

Internet

http://link.springer.com/article/10.1186/s42162-018-0009-3

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