| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_d9ae7582c5f887bc2e8f656b4e0fc52a |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q50-01 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F40-58
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F17-2854
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F17-289
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F40-44
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F40-51 |
| classificationIPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q50-00 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F17-28
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F40-00 |
| filingDate |
2016-06-24-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate |
2018-10-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_bb1dccfd2b19775d78d92227a56c32b1
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7db514ddb8f567f1fa4b025f50f62d3f
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9391d0545d5af79e3d6e8802edc7ca34
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_fd6fdc7f7faf8bb6cc735d9a91d8b1ce |
| publicationDate |
2018-10-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-10114819-B2 |
| titleOfInvention |
Optimizing machine translations for user engagement |
| abstract |
Exemplary embodiments relate to techniques for improving a machine translation system. The machine translation system may include one or more models for generating a translation. The system may generate multiple candidate translations, and may present the candidate translations to different groups of users, such as users of a social network. User engagement with the different candidate translations may be measured, and the system may determine which of the candidate translations was most favored by the users. For example, in the context of a social network, the number of times that the translation is liked or shared, or the number of comments associated with the translation, may be used to determine user engagement with the translation. The models of the machine translation system may be modified to favor the most-favored candidate translation. The translation system may repeat this process to continue to tune the models in a feedback loop. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11429795-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-10366171-B1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-10733387-B1 |
| priorityDate |
2016-06-24-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |