| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_7fa2a002b2217830b670e2b42f923139 |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F2201-86 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F11-3065
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-70
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F11-3409
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F11-2263
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F11-22
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F11-3495
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F11-3452
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F11-30
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/G06K9-6215
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06K9-6267 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F11-34
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F11-30
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F11-22 |
| filingDate |
2020-01-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate |
2022-05-24-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_839b9c0f74af2f8156ba444ce2105262
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_5f0c389f3faf6343c038291e7ca26216
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_10bb2a81ecaec03e997637e8df594c82
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f1ba40381562dfa64b924a53b7078361 |
| publicationDate |
2022-05-24-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-11341026-B2 |
| titleOfInvention |
Facilitating detection of anomalies in data center telemetry |
| abstract |
Facilitating detection of anomalies of a target entity is provided herein. A system can comprise a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. The operations can comprise training a model on a first set of variables that are constrained by a second set of variables. The second set of variables can characterize elements of a defined entity. The first set of variables can define a normality of the defined entity. The operations also can comprise employing the model to identify expected parameters and unexpected parameters associated with the defined entity to at least a defined level of confidence. |
| priorityDate |
2020-01-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |