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The LEJO project aims to enhance spatial data processing through machine learning techniques. By developing new methods for spatial joins, the research seeks to improve efficiency in applications such as traffic management and robotics.
Arguably 80% of all data is spatial.
This calls for highly efficient and effective spatial data operations.
Among them, spatial joins are frequently needed as a key primitive in various applications such as traffic management, robotics control, location-based services and even human brain modelling.
However, existing spatial join approaches follow the traditional filter-and-refinement paradigm that is data distribution-oblivious.
As a result, existing approaches are increasingly inefficient as s…
ROSKILDE UNIVERSITET
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Germany, Berlin
Type: University / higher education
Activity type: Higher or Secondary Education Establishments
SME: No
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