| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_7542cdde926ccc0ad7b27ea92c083088 |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61M2021-0083
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61M2205-3592
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61M2205-50
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61M2205-3584
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61M2205-332
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61M2230-63
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61M2205-3553 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F16-24575
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F16-24578
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61M21-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q50-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q10-1095
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-025
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N7-00 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61M21-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q10-00 |
| filingDate |
2016-04-28-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_298144150d647b6b3f3a3635d2df1b23
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2d56dfae8c36232f0117af6a9a4020a0
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_019ca135bd103803dbf20085ee21ddba
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9e45b615131e1392f2be88f13a00e2c1
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_ae66c203dda87be356b965d191fb5c6b |
| publicationDate |
2018-03-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
EP-3288622-A1 |
| titleOfInvention |
Unusualness of events based on user routine models |
| abstract |
In some implementations, sensors provide sensor data reflecting user activity detected by the sensors. An event analyzer generates an unusualness score for an event associated with a user based on routine-related aspects generated from one or more user routine models associated with the user. The one or more user routine models are trained based at least in part on interaction data comprised of the sensor data. Event attributes of the event can be received that include a time of the event and attendees of the event. The unusualness score may be generated by analyzing the event attributes with respect to the routine-related aspects. The unusualness score is generated to quantify a level of deviation between the event attributes and the routine-related aspects. Service content can be generated for the user based at least in part on the unusualness score generated for the event. |
| priorityDate |
2015-04-29-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |