Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems
The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems ("MLUI") transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections...
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Patent |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | Neto, Manuel De Araujo Pedreira Snyder, Jason Alan Gorman, Stephen Michael Klau Silverman, Elena Clark, Michael |
| description | The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems ("MLUI") transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier. CI datapoint values corresponding to the set of visualization CI datapoint identifiers are retrieved from a NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data. A visualization is generated using the retrieved CI datapoint values. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US11694119B1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US11694119B1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US11694119B13</originalsourceid><addsrcrecordid>eNqNzDEOwjAMheEuDAi4g9lhiEBIXUEgFiZgrqzGTSMlTojdgdvTIg7A9Jbvf_PqdRuCeusjsfjEGCBi23smCISFPTuwqAjIFgahAp6VSoctgZAbKwVF5yZH7KYOc8aCOmLZQCTtk5VvLm9RirKsZh0GodVvF9X6cn6crlvKqSHJ4zWTNs-7MYd6b0x9NLt_zAcKIESI</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems</title><source>esp@cenet</source><creator>Neto, Manuel De Araujo Pedreira ; Snyder, Jason Alan ; Gorman, Stephen Michael ; Klau Silverman, Elena ; Clark, Michael</creator><creatorcontrib>Neto, Manuel De Araujo Pedreira ; Snyder, Jason Alan ; Gorman, Stephen Michael ; Klau Silverman, Elena ; Clark, Michael</creatorcontrib><description>The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems ("MLUI") transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier. CI datapoint values corresponding to the set of visualization CI datapoint identifiers are retrieved from a NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data. A visualization is generated using the retrieved CI datapoint values.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230704&DB=EPODOC&CC=US&NR=11694119B1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230704&DB=EPODOC&CC=US&NR=11694119B1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Neto, Manuel De Araujo Pedreira</creatorcontrib><creatorcontrib>Snyder, Jason Alan</creatorcontrib><creatorcontrib>Gorman, Stephen Michael</creatorcontrib><creatorcontrib>Klau Silverman, Elena</creatorcontrib><creatorcontrib>Clark, Michael</creatorcontrib><title>Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems</title><description>The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems ("MLUI") transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier. CI datapoint values corresponding to the set of visualization CI datapoint identifiers are retrieved from a NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data. A visualization is generated using the retrieved CI datapoint values.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNzDEOwjAMheEuDAi4g9lhiEBIXUEgFiZgrqzGTSMlTojdgdvTIg7A9Jbvf_PqdRuCeusjsfjEGCBi23smCISFPTuwqAjIFgahAp6VSoctgZAbKwVF5yZH7KYOc8aCOmLZQCTtk5VvLm9RirKsZh0GodVvF9X6cn6crlvKqSHJ4zWTNs-7MYd6b0x9NLt_zAcKIESI</recordid><startdate>20230704</startdate><enddate>20230704</enddate><creator>Neto, Manuel De Araujo Pedreira</creator><creator>Snyder, Jason Alan</creator><creator>Gorman, Stephen Michael</creator><creator>Klau Silverman, Elena</creator><creator>Clark, Michael</creator><scope>EVB</scope></search><sort><creationdate>20230704</creationdate><title>Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems</title><author>Neto, Manuel De Araujo Pedreira ; Snyder, Jason Alan ; Gorman, Stephen Michael ; Klau Silverman, Elena ; Clark, Michael</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US11694119B13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>Neto, Manuel De Araujo Pedreira</creatorcontrib><creatorcontrib>Snyder, Jason Alan</creatorcontrib><creatorcontrib>Gorman, Stephen Michael</creatorcontrib><creatorcontrib>Klau Silverman, Elena</creatorcontrib><creatorcontrib>Clark, Michael</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Neto, Manuel De Araujo Pedreira</au><au>Snyder, Jason Alan</au><au>Gorman, Stephen Michael</au><au>Klau Silverman, Elena</au><au>Clark, Michael</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems</title><date>2023-07-04</date><risdate>2023</risdate><abstract>The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems ("MLUI") transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier. CI datapoint values corresponding to the set of visualization CI datapoint identifiers are retrieved from a NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data. A visualization is generated using the retrieved CI datapoint values.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_US11694119B1 |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T14%3A38%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Neto,%20Manuel%20De%20Araujo%20Pedreira&rft.date=2023-07-04&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS11694119B1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |