http://rdf.ncbi.nlm.nih.gov/pubchem/patent/JP-2021534483-A

Outgoing Links

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classificationCPCAdditional http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N7-01
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F17-18
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2178
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F21-6245
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-22
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-025
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q10-10
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F16-35
filingDate 2019-08-13-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationDate 2021-12-09-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber JP-2021534483-A
titleOfInvention Machine learning systems and methods to determine the reliability level of personal information survey results
abstract Privacy to scan any number of data sources to visualize stored personal information, risks associated with the storage of such personal information, and / or usage activities related to such information to the user. The management platform is disclosed. The platform may correlate personal information results with specific data subjects and uses machine learning models to classify the results as corresponding to specific personal information attributes and index across multiple data sources. You may provide the inventory that has been done.
priorityDate 2018-08-13-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

Incoming Links

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isDiscussedBy http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID415828001
http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID130640

Total number of triples: 20.