| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_5bf7a0997c5ecffc9035f9619bad0c0b |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q30-0202
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24133
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q30-02
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N99-00 |
| filingDate |
2017-12-21-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_55060a716d9710d40280074153997e46
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_464d126e91c2d1f685799301eacf4a7e
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7a462210555670ac1397f6757f8f30fa
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_97b89515345442233e677698e4dbdcae |
| publicationDate |
2018-06-08-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-108133387-A |
| titleOfInvention |
Multi-label K-Nearest Neighbor Algorithm Based on Soft Information |
| abstract |
The present invention is a multi-label K-nearest neighbor algorithm based on soft information. The problem to be solved is how to optimize the classic multi-label K-nearest neighbor learning algorithm according to the requirements and characteristics of actual big data application scenarios to obtain better classification performance and higher efficiency. computational complexity. The invention increases the use of soft information to improve the generalization performance of the algorithm, and is especially suitable for the application scenario of mobile Internet service perception KQI index prediction. Based on massive historical labeled data, it predicts the labels under specific attribute conditions, which provides better classification prediction performance and higher learning efficiency than the traditional ML-kNN algorithm. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109102006-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109102006-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110049129-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109379763-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109379763-B |
| priorityDate |
2017-12-21-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |