Subject line tester
Methods, systems, and devices supporting data processing are described. In some systems, a data processing platform may support communication message analysis using machine learning. For example, a system may receive a set of communication messages (e.g., social media messages) and perform a machine...
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 | Wilson, Daniel Keith Brewer, James Mallick, Shrestha Basu Belkowitz, Jonathan Daniel Showers Stadlinger, Peter Cagrici, Gokhan Gasperut, Daniel Louis Black, Evan Brewer, Michael Ronald Lestina, Jason Xie, Kexin Zickgraf, Jeffery Allen Lyman, Greg Trepina, Matthew David Schultz, Victoria Rauschuber, Austin |
| description | Methods, systems, and devices supporting data processing are described. In some systems, a data processing platform may support communication message analysis using machine learning. For example, a system may receive a set of communication messages (e.g., social media messages) and perform a machine learning process on the message contents and message interaction data to train a machine learned model. The system may further receive a subject line for a communication message for analysis, input the subject line into the machine learned model, and receive, as an output of the machine learned model, an engagement score based on the subject line. The engagement score may indicate an estimated probability that a user receiving the communication message opens the communication message (e.g., based on the subject line). A user-or the system-may modify the subject line based on the analysis to improve the engagement score. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US11475207B2</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US11475207B2</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US11475207B23</originalsourceid><addsrcrecordid>eNrjZBAOLk3KSk0uUcjJzEtVKEktLkkt4mFgTUvMKU7lhdLcDIpuriHOHrqpBfnxqcUFicmpeakl8aHBhoYm5qZGBuZORsbEqAEAH_Ygcw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Subject line tester</title><source>esp@cenet</source><creator>Wilson, Daniel Keith ; Brewer, James ; Mallick, Shrestha Basu ; Belkowitz, Jonathan Daniel Showers ; Stadlinger, Peter ; Cagrici, Gokhan ; Gasperut, Daniel Louis ; Black, Evan ; Brewer, Michael Ronald ; Lestina, Jason ; Xie, Kexin ; Zickgraf, Jeffery Allen ; Lyman, Greg ; Trepina, Matthew David ; Schultz, Victoria ; Rauschuber, Austin</creator><creatorcontrib>Wilson, Daniel Keith ; Brewer, James ; Mallick, Shrestha Basu ; Belkowitz, Jonathan Daniel Showers ; Stadlinger, Peter ; Cagrici, Gokhan ; Gasperut, Daniel Louis ; Black, Evan ; Brewer, Michael Ronald ; Lestina, Jason ; Xie, Kexin ; Zickgraf, Jeffery Allen ; Lyman, Greg ; Trepina, Matthew David ; Schultz, Victoria ; Rauschuber, Austin</creatorcontrib><description>Methods, systems, and devices supporting data processing are described. In some systems, a data processing platform may support communication message analysis using machine learning. For example, a system may receive a set of communication messages (e.g., social media messages) and perform a machine learning process on the message contents and message interaction data to train a machine learned model. The system may further receive a subject line for a communication message for analysis, input the subject line into the machine learned model, and receive, as an output of the machine learned model, an engagement score based on the subject line. The engagement score may indicate an estimated probability that a user receiving the communication message opens the communication message (e.g., based on the subject line). A user-or the system-may modify the subject line based on the analysis to improve the engagement score.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRIC DIGITAL DATA PROCESSING ; ELECTRICITY ; PHYSICS ; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><creationdate>2022</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=20221018&DB=EPODOC&CC=US&NR=11475207B2$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76318</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20221018&DB=EPODOC&CC=US&NR=11475207B2$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Wilson, Daniel Keith</creatorcontrib><creatorcontrib>Brewer, James</creatorcontrib><creatorcontrib>Mallick, Shrestha Basu</creatorcontrib><creatorcontrib>Belkowitz, Jonathan Daniel Showers</creatorcontrib><creatorcontrib>Stadlinger, Peter</creatorcontrib><creatorcontrib>Cagrici, Gokhan</creatorcontrib><creatorcontrib>Gasperut, Daniel Louis</creatorcontrib><creatorcontrib>Black, Evan</creatorcontrib><creatorcontrib>Brewer, Michael Ronald</creatorcontrib><creatorcontrib>Lestina, Jason</creatorcontrib><creatorcontrib>Xie, Kexin</creatorcontrib><creatorcontrib>Zickgraf, Jeffery Allen</creatorcontrib><creatorcontrib>Lyman, Greg</creatorcontrib><creatorcontrib>Trepina, Matthew David</creatorcontrib><creatorcontrib>Schultz, Victoria</creatorcontrib><creatorcontrib>Rauschuber, Austin</creatorcontrib><title>Subject line tester</title><description>Methods, systems, and devices supporting data processing are described. In some systems, a data processing platform may support communication message analysis using machine learning. For example, a system may receive a set of communication messages (e.g., social media messages) and perform a machine learning process on the message contents and message interaction data to train a machine learned model. The system may further receive a subject line for a communication message for analysis, input the subject line into the machine learned model, and receive, as an output of the machine learned model, an engagement score based on the subject line. The engagement score may indicate an estimated probability that a user receiving the communication message opens the communication message (e.g., based on the subject line). A user-or the system-may modify the subject line based on the analysis to improve the engagement score.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC COMMUNICATION TECHNIQUE</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>ELECTRICITY</subject><subject>PHYSICS</subject><subject>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZBAOLk3KSk0uUcjJzEtVKEktLkkt4mFgTUvMKU7lhdLcDIpuriHOHrqpBfnxqcUFicmpeakl8aHBhoYm5qZGBuZORsbEqAEAH_Ygcw</recordid><startdate>20221018</startdate><enddate>20221018</enddate><creator>Wilson, Daniel Keith</creator><creator>Brewer, James</creator><creator>Mallick, Shrestha Basu</creator><creator>Belkowitz, Jonathan Daniel Showers</creator><creator>Stadlinger, Peter</creator><creator>Cagrici, Gokhan</creator><creator>Gasperut, Daniel Louis</creator><creator>Black, Evan</creator><creator>Brewer, Michael Ronald</creator><creator>Lestina, Jason</creator><creator>Xie, Kexin</creator><creator>Zickgraf, Jeffery Allen</creator><creator>Lyman, Greg</creator><creator>Trepina, Matthew David</creator><creator>Schultz, Victoria</creator><creator>Rauschuber, Austin</creator><scope>EVB</scope></search><sort><creationdate>20221018</creationdate><title>Subject line tester</title><author>Wilson, Daniel Keith ; Brewer, James ; Mallick, Shrestha Basu ; Belkowitz, Jonathan Daniel Showers ; Stadlinger, Peter ; Cagrici, Gokhan ; Gasperut, Daniel Louis ; Black, Evan ; Brewer, Michael Ronald ; Lestina, Jason ; Xie, Kexin ; Zickgraf, Jeffery Allen ; Lyman, Greg ; Trepina, Matthew David ; Schultz, Victoria ; Rauschuber, Austin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US11475207B23</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC COMMUNICATION TECHNIQUE</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>ELECTRICITY</topic><topic>PHYSICS</topic><topic>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</topic><toplevel>online_resources</toplevel><creatorcontrib>Wilson, Daniel Keith</creatorcontrib><creatorcontrib>Brewer, James</creatorcontrib><creatorcontrib>Mallick, Shrestha Basu</creatorcontrib><creatorcontrib>Belkowitz, Jonathan Daniel Showers</creatorcontrib><creatorcontrib>Stadlinger, Peter</creatorcontrib><creatorcontrib>Cagrici, Gokhan</creatorcontrib><creatorcontrib>Gasperut, Daniel Louis</creatorcontrib><creatorcontrib>Black, Evan</creatorcontrib><creatorcontrib>Brewer, Michael Ronald</creatorcontrib><creatorcontrib>Lestina, Jason</creatorcontrib><creatorcontrib>Xie, Kexin</creatorcontrib><creatorcontrib>Zickgraf, Jeffery Allen</creatorcontrib><creatorcontrib>Lyman, Greg</creatorcontrib><creatorcontrib>Trepina, Matthew David</creatorcontrib><creatorcontrib>Schultz, Victoria</creatorcontrib><creatorcontrib>Rauschuber, Austin</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wilson, Daniel Keith</au><au>Brewer, James</au><au>Mallick, Shrestha Basu</au><au>Belkowitz, Jonathan Daniel Showers</au><au>Stadlinger, Peter</au><au>Cagrici, Gokhan</au><au>Gasperut, Daniel Louis</au><au>Black, Evan</au><au>Brewer, Michael Ronald</au><au>Lestina, Jason</au><au>Xie, Kexin</au><au>Zickgraf, Jeffery Allen</au><au>Lyman, Greg</au><au>Trepina, Matthew David</au><au>Schultz, Victoria</au><au>Rauschuber, Austin</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Subject line tester</title><date>2022-10-18</date><risdate>2022</risdate><abstract>Methods, systems, and devices supporting data processing are described. In some systems, a data processing platform may support communication message analysis using machine learning. For example, a system may receive a set of communication messages (e.g., social media messages) and perform a machine learning process on the message contents and message interaction data to train a machine learned model. The system may further receive a subject line for a communication message for analysis, input the subject line into the machine learned model, and receive, as an output of the machine learned model, an engagement score based on the subject line. The engagement score may indicate an estimated probability that a user receiving the communication message opens the communication message (e.g., based on the subject line). A user-or the system-may modify the subject line based on the analysis to improve the engagement score.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_US11475207B2 |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY PHYSICS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
| title | Subject line tester |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T08%3A41%3A11IST&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=Wilson,%20Daniel%20Keith&rft.date=2022-10-18&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS11475207B2%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 |