E-commerce session recommendation method, system and device based on multi-behavior feature fusion and medium

The invention discloses an e-commerce session recommendation method and system based on multi-behavior feature fusion. The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-comm...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: DING JIAWEI, BAO BINGKUN, LU GUANMING, YU PENGHANG
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 DING JIAWEI
BAO BINGKUN
LU GUANMING
YU PENGHANG
description The invention discloses an e-commerce session recommendation method and system based on multi-behavior feature fusion. The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-commerce database; an electronic commerce session recommendation model based on multi-behavior feature fusion is constructed, and the model comprises a behavior feature extraction module, a commodity feature extraction module, a commodity high-order feature extraction module, a session feature extraction module and a commodity recommendation module; four kinds of session behavior data in an e-commerce database are used for training the e-commerce session recommendation model; and utilizing the trained e-commerce session recommendation model to carry out commodity recommendation on users in the session, and outputting a recommendation result. The multi-behavior characteristics in the session are fused by using the e-com
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN115659277A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN115659277A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN115659277A3</originalsourceid><addsrcrecordid>eNqNjDEOgkAURGksjHqHby8FGiSUhmCsrOzJwg5hE_4u2b9L4u0V4gGsJjN5b7YJ12nnmOE7kEDEOEse62S1CktlhMHpE8lbApiU1aQxm6_QKoGmBYljMGmLQc3GeeqhQvSgPq5_i8HQJvI-2fRqFBx-uUuO9_pVPVJMroFMqoNFaKpnluXXvDwXxe3yD_MBekNCTQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>E-commerce session recommendation method, system and device based on multi-behavior feature fusion and medium</title><source>esp@cenet</source><creator>DING JIAWEI ; BAO BINGKUN ; LU GUANMING ; YU PENGHANG</creator><creatorcontrib>DING JIAWEI ; BAO BINGKUN ; LU GUANMING ; YU PENGHANG</creatorcontrib><description>The invention discloses an e-commerce session recommendation method and system based on multi-behavior feature fusion. The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-commerce database; an electronic commerce session recommendation model based on multi-behavior feature fusion is constructed, and the model comprises a behavior feature extraction module, a commodity feature extraction module, a commodity high-order feature extraction module, a session feature extraction module and a commodity recommendation module; four kinds of session behavior data in an e-commerce database are used for training the e-commerce session recommendation model; and utilizing the trained e-commerce session recommendation model to carry out commodity recommendation on users in the session, and outputting a recommendation result. The multi-behavior characteristics in the session are fused by using the e-com</description><language>chi ; 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&amp;date=20230131&amp;DB=EPODOC&amp;CC=CN&amp;NR=115659277A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,778,883,25551,76302</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20230131&amp;DB=EPODOC&amp;CC=CN&amp;NR=115659277A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>DING JIAWEI</creatorcontrib><creatorcontrib>BAO BINGKUN</creatorcontrib><creatorcontrib>LU GUANMING</creatorcontrib><creatorcontrib>YU PENGHANG</creatorcontrib><title>E-commerce session recommendation method, system and device based on multi-behavior feature fusion and medium</title><description>The invention discloses an e-commerce session recommendation method and system based on multi-behavior feature fusion. The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-commerce database; an electronic commerce session recommendation model based on multi-behavior feature fusion is constructed, and the model comprises a behavior feature extraction module, a commodity feature extraction module, a commodity high-order feature extraction module, a session feature extraction module and a commodity recommendation module; four kinds of session behavior data in an e-commerce database are used for training the e-commerce session recommendation model; and utilizing the trained e-commerce session recommendation model to carry out commodity recommendation on users in the session, and outputting a recommendation result. The multi-behavior characteristics in the session are fused by using the e-com</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>eNqNjDEOgkAURGksjHqHby8FGiSUhmCsrOzJwg5hE_4u2b9L4u0V4gGsJjN5b7YJ12nnmOE7kEDEOEse62S1CktlhMHpE8lbApiU1aQxm6_QKoGmBYljMGmLQc3GeeqhQvSgPq5_i8HQJvI-2fRqFBx-uUuO9_pVPVJMroFMqoNFaKpnluXXvDwXxe3yD_MBekNCTQ</recordid><startdate>20230131</startdate><enddate>20230131</enddate><creator>DING JIAWEI</creator><creator>BAO BINGKUN</creator><creator>LU GUANMING</creator><creator>YU PENGHANG</creator><scope>EVB</scope></search><sort><creationdate>20230131</creationdate><title>E-commerce session recommendation method, system and device based on multi-behavior feature fusion and medium</title><author>DING JIAWEI ; BAO BINGKUN ; LU GUANMING ; YU PENGHANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN115659277A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; 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>DING JIAWEI</creatorcontrib><creatorcontrib>BAO BINGKUN</creatorcontrib><creatorcontrib>LU GUANMING</creatorcontrib><creatorcontrib>YU PENGHANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>DING JIAWEI</au><au>BAO BINGKUN</au><au>LU GUANMING</au><au>YU PENGHANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>E-commerce session recommendation method, system and device based on multi-behavior feature fusion and medium</title><date>2023-01-31</date><risdate>2023</risdate><abstract>The invention discloses an e-commerce session recommendation method and system based on multi-behavior feature fusion. The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-commerce database; an electronic commerce session recommendation model based on multi-behavior feature fusion is constructed, and the model comprises a behavior feature extraction module, a commodity feature extraction module, a commodity high-order feature extraction module, a session feature extraction module and a commodity recommendation module; four kinds of session behavior data in an e-commerce database are used for training the e-commerce session recommendation model; and utilizing the trained e-commerce session recommendation model to carry out commodity recommendation on users in the session, and outputting a recommendation result. The multi-behavior characteristics in the session are fused by using the e-com</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN115659277A
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 E-commerce session recommendation method, system and device based on multi-behavior feature fusion and medium
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T15%3A31%3A36IST&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=DING%20JIAWEI&rft.date=2023-01-31&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN115659277A%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