NEURAL NETWORK PROCESSING OF RETURN PATH DATA TO ESTIMATE HOUSEHOLD MEMBER AND VISITOR DEMOGRAPHICS

Example demographic estimation systems disclosed herein include a feature generator to generate features from return path data reported from set-top boxes associated with return path data households; a neural network to process the features generated from the return path data to predict demographic...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: KURZYNSKI, David J
Format: Patent
Sprache:eng ; fre ; ger
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 KURZYNSKI, David J
description Example demographic estimation systems disclosed herein include a feature generator to generate features from return path data reported from set-top boxes associated with return path data households; a neural network to process the features generated from the return path data to predict demographic classification probabilities for the return path data households, the neural network to be trained based on panel data reported from meters that monitor media devices associated with panelist households; a demographic assignment engine to assign one or more demographic categories to respective ones of the return path data households based on the predicted demographic classification probabilities; and a visitor assignment engine to assign virtual visitors to at least a subset of the respective ones of the return path data households based on the one or more demographic categories assigned to the respective ones of the return path data households.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_EP3963894A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>EP3963894A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_EP3963894A13</originalsourceid><addsrcrecordid>eNqNyrEKwjAQANAuDqL-w_2Ag1TEjmdzbYJNLlyuOpZS4iRaqP-Pix_g9Ja3LqZAvWAHgfTOcoUoXFNKLrTADQhpLwEiqgWDiqAMlNR5VALLfSLLnQFP_kICGAzcXHLKAoY8t4LRujpti9VjfC5593NTQENa232e30Ne5nHKr_wZKJbVqTxXRzyUf5Qv1vw0Kw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>NEURAL NETWORK PROCESSING OF RETURN PATH DATA TO ESTIMATE HOUSEHOLD MEMBER AND VISITOR DEMOGRAPHICS</title><source>esp@cenet</source><creator>KURZYNSKI, David J</creator><creatorcontrib>KURZYNSKI, David J</creatorcontrib><description>Example demographic estimation systems disclosed herein include a feature generator to generate features from return path data reported from set-top boxes associated with return path data households; a neural network to process the features generated from the return path data to predict demographic classification probabilities for the return path data households, the neural network to be trained based on panel data reported from meters that monitor media devices associated with panelist households; a demographic assignment engine to assign one or more demographic categories to respective ones of the return path data households based on the predicted demographic classification probabilities; and a visitor assignment engine to assign virtual visitors to at least a subset of the respective ones of the return path data households based on the one or more demographic categories assigned to the respective ones of the return path data households.</description><language>eng ; fre ; ger</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRICITY ; PHYSICS ; PICTORIAL COMMUNICATION, e.g. TELEVISION</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&amp;date=20220309&amp;DB=EPODOC&amp;CC=EP&amp;NR=3963894A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20220309&amp;DB=EPODOC&amp;CC=EP&amp;NR=3963894A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>KURZYNSKI, David J</creatorcontrib><title>NEURAL NETWORK PROCESSING OF RETURN PATH DATA TO ESTIMATE HOUSEHOLD MEMBER AND VISITOR DEMOGRAPHICS</title><description>Example demographic estimation systems disclosed herein include a feature generator to generate features from return path data reported from set-top boxes associated with return path data households; a neural network to process the features generated from the return path data to predict demographic classification probabilities for the return path data households, the neural network to be trained based on panel data reported from meters that monitor media devices associated with panelist households; a demographic assignment engine to assign one or more demographic categories to respective ones of the return path data households based on the predicted demographic classification probabilities; and a visitor assignment engine to assign virtual visitors to at least a subset of the respective ones of the return path data households based on the one or more demographic categories assigned to the respective ones of the return path data households.</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>ELECTRICITY</subject><subject>PHYSICS</subject><subject>PICTORIAL COMMUNICATION, e.g. TELEVISION</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyrEKwjAQANAuDqL-w_2Ag1TEjmdzbYJNLlyuOpZS4iRaqP-Pix_g9Ja3LqZAvWAHgfTOcoUoXFNKLrTADQhpLwEiqgWDiqAMlNR5VALLfSLLnQFP_kICGAzcXHLKAoY8t4LRujpti9VjfC5593NTQENa232e30Ne5nHKr_wZKJbVqTxXRzyUf5Qv1vw0Kw</recordid><startdate>20220309</startdate><enddate>20220309</enddate><creator>KURZYNSKI, David J</creator><scope>EVB</scope></search><sort><creationdate>20220309</creationdate><title>NEURAL NETWORK PROCESSING OF RETURN PATH DATA TO ESTIMATE HOUSEHOLD MEMBER AND VISITOR DEMOGRAPHICS</title><author>KURZYNSKI, David J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_EP3963894A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre ; ger</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>ELECTRICITY</topic><topic>PHYSICS</topic><topic>PICTORIAL COMMUNICATION, e.g. TELEVISION</topic><toplevel>online_resources</toplevel><creatorcontrib>KURZYNSKI, David J</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>KURZYNSKI, David J</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>NEURAL NETWORK PROCESSING OF RETURN PATH DATA TO ESTIMATE HOUSEHOLD MEMBER AND VISITOR DEMOGRAPHICS</title><date>2022-03-09</date><risdate>2022</risdate><abstract>Example demographic estimation systems disclosed herein include a feature generator to generate features from return path data reported from set-top boxes associated with return path data households; a neural network to process the features generated from the return path data to predict demographic classification probabilities for the return path data households, the neural network to be trained based on panel data reported from meters that monitor media devices associated with panelist households; a demographic assignment engine to assign one or more demographic categories to respective ones of the return path data households based on the predicted demographic classification probabilities; and a visitor assignment engine to assign virtual visitors to at least a subset of the respective ones of the return path data households based on the one or more demographic categories assigned to the respective ones of the return path data households.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng ; fre ; ger
recordid cdi_epo_espacenet_EP3963894A1
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
PHYSICS
PICTORIAL COMMUNICATION, e.g. TELEVISION
title NEURAL NETWORK PROCESSING OF RETURN PATH DATA TO ESTIMATE HOUSEHOLD MEMBER AND VISITOR DEMOGRAPHICS
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T07%3A59%3A58IST&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=KURZYNSKI,%20David%20J&rft.date=2022-03-09&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EEP3963894A1%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