Bidirectional Gated Recurrent Unit Neural Network for Chinese Address Element Segmentation

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datacite.relatedItem.firstPage635
datacite.relatedItem.issue11
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2220-9964
datacite.relatedItem.relationTypeIsPublishedIn
datacite.relatedItem.titleIJGI
datacite.relatedItem.volume9
dc.contributor.authorPengpeng Li
dc.contributor.authorAn Luo
dc.contributor.authorJiping Liu
dc.contributor.authorYong Wang
dc.contributor.authorJun Zhu
dc.contributor.authorYue Deng
dc.contributor.authorJunjie Zhang
dc.date.accessioned2025-05-14T16:46:27Z
dc.date.available2025-05-14T16:46:27Z
dc.date.issued2020
dc.identifier.doihttps://doi.org/10.3390/ijgi9110635
dc.identifier.otherjz000157-0627
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/32116
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc550
dc.titleBidirectional Gated Recurrent Unit Neural Network for Chinese Address Element Segmentation
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/32117
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