User interest analysis method based on e-commerce big data
The invention discloses a user interest analysis method based on e-commerce big data, and the method comprises the following steps: S1, constructing a data model of a user based on the type score through the e-commerce big data, determining a type set in which the user is interested according to the...
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| creator | XIAO JIWEN SHAO CHENGLONG TAO SHUAI |
| description | The invention discloses a user interest analysis method based on e-commerce big data, and the method comprises the following steps: S1, constructing a data model of a user based on the type score through the e-commerce big data, determining a type set in which the user is interested according to the type score, and carrying out the scoring of a commodity containing a preference type through the preference type of the user; s2, based on the score vector, recording the user purchase behavior as an event vector occurring according to a time sequence, rearranging scores of each type according to a time sequence direction, and establishing a score matrix according to the scores of each type; and S3, variance fluctuation characteristics generated in different stages are adjusted through a time attenuation factor, user interest data trend characteristics are determined according to convergence degrees of the variance fluctuation characteristics, and prediction accuracy can be effectively improved by combining time s |
| format | Patent |
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s2, based on the score vector, recording the user purchase behavior as an event vector occurring according to a time sequence, rearranging scores of each type according to a time sequence direction, and establishing a score matrix according to the scores of each type; and S3, variance fluctuation characteristics generated in different stages are adjusted through a time attenuation factor, user interest data trend characteristics are determined according to convergence degrees of the variance fluctuation characteristics, and prediction accuracy can be effectively improved by combining time s</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; 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=20230926&DB=EPODOC&CC=CN&NR=116805257A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,778,883,25551,76302</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230926&DB=EPODOC&CC=CN&NR=116805257A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>XIAO JIWEN</creatorcontrib><creatorcontrib>SHAO CHENGLONG</creatorcontrib><creatorcontrib>TAO SHUAI</creatorcontrib><title>User interest analysis method based on e-commerce big data</title><description>The invention discloses a user interest analysis method based on e-commerce big data, and the method comprises the following steps: S1, constructing a data model of a user based on the type score through the e-commerce big data, determining a type set in which the user is interested according to the type score, and carrying out the scoring of a commodity containing a preference type through the preference type of the user; s2, based on the score vector, recording the user purchase behavior as an event vector occurring according to a time sequence, rearranging scores of each type according to a time sequence direction, and establishing a score matrix according to the scores of each type; and S3, variance fluctuation characteristics generated in different stages are adjusted through a time attenuation factor, user interest data trend characteristics are determined according to convergence degrees of the variance fluctuation characteristics, and prediction accuracy can be effectively improved by combining time s</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>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>eNrjZLAKLU4tUsjMK0ktSi0uUUjMS8ypLM4sVshNLcnIT1FISixOTVHIz1NI1U3Oz81NLUpOVUjKTFdISSxJ5GFgTUvMKU7lhdLcDIpuriHOHrqpBfnxqcUFicmpeakl8c5-hoZmFgamRqbmjsbEqAEAUUkung</recordid><startdate>20230926</startdate><enddate>20230926</enddate><creator>XIAO JIWEN</creator><creator>SHAO CHENGLONG</creator><creator>TAO SHUAI</creator><scope>EVB</scope></search><sort><creationdate>20230926</creationdate><title>User interest analysis method based on e-commerce big data</title><author>XIAO JIWEN ; SHAO CHENGLONG ; TAO SHUAI</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116805257A3</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>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>XIAO JIWEN</creatorcontrib><creatorcontrib>SHAO CHENGLONG</creatorcontrib><creatorcontrib>TAO SHUAI</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>XIAO JIWEN</au><au>SHAO CHENGLONG</au><au>TAO SHUAI</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>User interest analysis method based on e-commerce big data</title><date>2023-09-26</date><risdate>2023</risdate><abstract>The invention discloses a user interest analysis method based on e-commerce big data, and the method comprises the following steps: S1, constructing a data model of a user based on the type score through the e-commerce big data, determining a type set in which the user is interested according to the type score, and carrying out the scoring of a commodity containing a preference type through the preference type of the user; s2, based on the score vector, recording the user purchase behavior as an event vector occurring according to a time sequence, rearranging scores of each type according to a time sequence direction, and establishing a score matrix according to the scores of each type; and S3, variance fluctuation characteristics generated in different stages are adjusted through a time attenuation factor, user interest data trend characteristics are determined according to convergence degrees of the variance fluctuation characteristics, and prediction accuracy can be effectively improved by combining time s</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | User interest analysis method based on e-commerce big data |
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