Model training method and device, computer equipment and storage medium
The invention discloses a model training method and device, computer equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining a training sample set; inputting each piece of sample user feature data into a first initial...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Patent |
| Sprache: | chi ; 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 | KONG TAOTAO SU CHANFEI LIN PENG |
| description | The invention discloses a model training method and device, computer equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining a training sample set; inputting each piece of sample user feature data into a first initial model to obtain a prediction label corresponding to each behavior prediction task; determining a first loss value corresponding to each behavior prediction task according to a difference degree between a prediction label corresponding to each behavior prediction task and a target label corresponding to each behavior prediction task; determining a total loss value based on the first loss value corresponding to each behavior prediction task; and according to the total loss value, carrying out iterative training on the first initial model until a first target condition is met, and obtaining the trained first initial model as a target marketing model. Thus, multi-task learning is adopted, the prediction capacity of th |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN115965463A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN115965463A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN115965463A3</originalsourceid><addsrcrecordid>eNrjZHD3zU9JzVEoKUrMzMvMS1fITS3JyE9RSMxLUUhJLctMTtVRSM7PLSgtSS1SSC0szSzITc0rAUsXl-QXJaanAnWkZJbm8jCwpiXmFKfyQmluBkU31xBnD93Ugvz41OKCxOTUvNSSeGc_Q0NTSzNTEzNjR2Ni1AAAW78z6w</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Model training method and device, computer equipment and storage medium</title><source>esp@cenet</source><creator>KONG TAOTAO ; SU CHANFEI ; LIN PENG</creator><creatorcontrib>KONG TAOTAO ; SU CHANFEI ; LIN PENG</creatorcontrib><description>The invention discloses a model training method and device, computer equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining a training sample set; inputting each piece of sample user feature data into a first initial model to obtain a prediction label corresponding to each behavior prediction task; determining a first loss value corresponding to each behavior prediction task according to a difference degree between a prediction label corresponding to each behavior prediction task and a target label corresponding to each behavior prediction task; determining a total loss value based on the first loss value corresponding to each behavior prediction task; and according to the total loss value, carrying out iterative training on the first initial model until a first target condition is met, and obtaining the trained first initial model as a target marketing model. Thus, multi-task learning is adopted, the prediction capacity of th</description><language>chi ; eng</language><subject>CALCULATING ; 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=20230414&DB=EPODOC&CC=CN&NR=115965463A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76419</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230414&DB=EPODOC&CC=CN&NR=115965463A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>KONG TAOTAO</creatorcontrib><creatorcontrib>SU CHANFEI</creatorcontrib><creatorcontrib>LIN PENG</creatorcontrib><title>Model training method and device, computer equipment and storage medium</title><description>The invention discloses a model training method and device, computer equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining a training sample set; inputting each piece of sample user feature data into a first initial model to obtain a prediction label corresponding to each behavior prediction task; determining a first loss value corresponding to each behavior prediction task according to a difference degree between a prediction label corresponding to each behavior prediction task and a target label corresponding to each behavior prediction task; determining a total loss value based on the first loss value corresponding to each behavior prediction task; and according to the total loss value, carrying out iterative training on the first initial model until a first target condition is met, and obtaining the trained first initial model as a target marketing model. Thus, multi-task learning is adopted, the prediction capacity of th</description><subject>CALCULATING</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>eNrjZHD3zU9JzVEoKUrMzMvMS1fITS3JyE9RSMxLUUhJLctMTtVRSM7PLSgtSS1SSC0szSzITc0rAUsXl-QXJaanAnWkZJbm8jCwpiXmFKfyQmluBkU31xBnD93Ugvz41OKCxOTUvNSSeGc_Q0NTSzNTEzNjR2Ni1AAAW78z6w</recordid><startdate>20230414</startdate><enddate>20230414</enddate><creator>KONG TAOTAO</creator><creator>SU CHANFEI</creator><creator>LIN PENG</creator><scope>EVB</scope></search><sort><creationdate>20230414</creationdate><title>Model training method and device, computer equipment and storage medium</title><author>KONG TAOTAO ; SU CHANFEI ; LIN PENG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN115965463A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</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>KONG TAOTAO</creatorcontrib><creatorcontrib>SU CHANFEI</creatorcontrib><creatorcontrib>LIN PENG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>KONG TAOTAO</au><au>SU CHANFEI</au><au>LIN PENG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Model training method and device, computer equipment and storage medium</title><date>2023-04-14</date><risdate>2023</risdate><abstract>The invention discloses a model training method and device, computer equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining a training sample set; inputting each piece of sample user feature data into a first initial model to obtain a prediction label corresponding to each behavior prediction task; determining a first loss value corresponding to each behavior prediction task according to a difference degree between a prediction label corresponding to each behavior prediction task and a target label corresponding to each behavior prediction task; determining a total loss value based on the first loss value corresponding to each behavior prediction task; and according to the total loss value, carrying out iterative training on the first initial model until a first target condition is met, and obtaining the trained first initial model as a target marketing model. Thus, multi-task learning is adopted, the prediction capacity of th</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN115965463A |
| source | esp@cenet |
| subjects | CALCULATING 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 | Model training method and device, computer equipment and storage medium |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T01%3A10%3A49IST&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=KONG%20TAOTAO&rft.date=2023-04-14&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN115965463A%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 |