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dc.contributor.authorGaikwad, Snehalkumar 'Neil'
dc.contributor.authorLunga, Dalton
dc.contributor.authorIyer, Shankar
dc.contributor.authorBondi, Elizabeth
dc.date.accessioned2022-10-24T13:24:58Z
dc.date.available2022-10-24T13:24:58Z
dc.date.issued2021-08-14
dc.identifier.isbn978-1-4503-8332-5
dc.identifier.urihttps://hdl.handle.net/1721.1/145948
dc.publisherACM|Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Miningen_US
dc.relation.isversionofhttps://doi-org.ezproxy.canberra.edu.au/10.1145/3447548.3469461en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceACM|Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Miningen_US
dc.titleData-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planningen_US
dc.typeArticleen_US
dc.identifier.citationGaikwad, Snehalkumar 'Neil', Lunga, Dalton, Iyer, Shankar and Bondi, Elizabeth. 2021. "Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning."
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratory
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-10-19T16:04:49Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2022-10-19T16:04:49Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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