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Dynamic Region Co-location Pattern Discovery: An Efficient Approach Based on Generalized Maximal Row Instances

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Published in:DSE
Format: Online Article RSS Article
Published: 2026
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discipline_display Technology & Engineering
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publishDate 2026
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spellingShingle Dynamic Region Co-location Pattern Discovery: An Efficient Approach Based on Generalized Maximal Row Instances
Big data and data science
Technology & Engineering — Computing
Technology & Engineering
sub_discipline_display Technology & Engineering — Computing
sub_discipline_facet Technology & Engineering — Computing
subject_display Big data and data science
Technology & Engineering — Computing
Technology & Engineering
Big data and data science
Technology & Engineering — Computing
Technology & Engineering
subject_facet Big data and data science
Technology & Engineering — Computing
Technology & Engineering
title Dynamic Region Co-location Pattern Discovery: An Efficient Approach Based on Generalized Maximal Row Instances
title_auth Dynamic Region Co-location Pattern Discovery: An Efficient Approach Based on Generalized Maximal Row Instances
title_full Dynamic Region Co-location Pattern Discovery: An Efficient Approach Based on Generalized Maximal Row Instances
title_fullStr Dynamic Region Co-location Pattern Discovery: An Efficient Approach Based on Generalized Maximal Row Instances
title_full_unstemmed Dynamic Region Co-location Pattern Discovery: An Efficient Approach Based on Generalized Maximal Row Instances
title_short Dynamic Region Co-location Pattern Discovery: An Efficient Approach Based on Generalized Maximal Row Instances
title_sort dynamic region co-location pattern discovery: an efficient approach based on generalized maximal row instances
topic Big data and data science
Technology & Engineering — Computing
Technology & Engineering
url https://link.springer.com/article/10.1007/s41019-025-00323-9