http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111382224-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_795cb009fbe52eb9be778ed97897534c |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-23 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F16-29 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F16-29 |
| filingDate | 2020-03-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2840c6615645a7383800953a634f186f http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_3e724aa8ae52dad8ab14f0c9def7a24d |
| publicationDate | 2020-07-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-111382224-A |
| titleOfInvention | An intelligent identification method of urban area functions based on multi-source data fusion |
| abstract | A method for intelligent identification of urban area functions based on multi-source data fusion of the present invention includes: acquiring map data of the city, dividing the city into several urban areas according to main roads; collecting interests contained in each urban area from Internet websites point metadata and text data and normalize; collect and quantify taxi trajectory data; build an unsupervised clustering model based on a Bayesian hierarchical model, and solve the model parameters according to variational inference; generate each city The topic distribution of the region, and the correlation between each topic and various functions, the most relevant urban functions of the topic with the highest probability are the main functions of the region; the most relevant urban feature words for each function in the region are generated. The method of the invention integrates multi-source and multi-modal data, intelligently identifies and divides urban area functions, generates two interpretation modes of function distribution and urban characteristics from numerical and text forms, and enhances the reliability and interpretability of urban area function identification. . |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113205042-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111966770-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114202039-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114202039-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112836121-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113205042-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112836121-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112487298-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114897444-A |
| priorityDate | 2020-03-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
| Predicate | Subject |
|---|---|
| isDiscussedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID28718 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419513094 |
Total number of triples: 26.