{"id":"https://openalex.org/W3217805968","doi":"https://doi.org/10.1109/etfa45728.2021.9613493","title":"A Model Fusion Approach for Goods Information Inspection in Dual-Platform E-Commerce Systems","display_name":"A Model Fusion Approach for Goods Information Inspection in Dual-Platform E-Commerce Systems","publication_year":2021,"publication_date":"2021-09-07","ids":{"openalex":"https://openalex.org/W3217805968","doi":"https://doi.org/10.1109/etfa45728.2021.9613493","mag":"3217805968"},"language":"en","primary_location":{"id":"doi:10.1109/etfa45728.2021.9613493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa45728.2021.9613493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100355768","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0002-0166-3944"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["JD Logistics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057045817","display_name":"Zhuozhuo Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuozhuo Zhao","raw_affiliation_strings":["JD Logistics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102019380","display_name":"Ting Jiang","orcid":"https://orcid.org/0000-0003-4925-2033"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Jiang","raw_affiliation_strings":["JD Logistics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445377","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0003-4219-781X"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Wang","raw_affiliation_strings":["JD Logistics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027912422","display_name":"Sheng\u2010Nan Wu","orcid":"https://orcid.org/0000-0002-5208-3253"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengnan Wu","raw_affiliation_strings":["JD Logistics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015611759","display_name":"Wenming Zhe","orcid":"https://orcid.org/0000-0003-1753-5784"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Zhe","raw_affiliation_strings":["JD Logistics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4198,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70833915,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"1","issue":null,"first_page":"01","last_page":"08"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9724000096321106,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9674999713897705,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7404911518096924},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5308077335357666},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5261311531066895}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7404911518096924},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5308077335357666},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5261311531066895},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/etfa45728.2021.9613493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa45728.2021.9613493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1614298861","https://openalex.org/W1840435438","https://openalex.org/W1902237438","https://openalex.org/W2053101950","https://openalex.org/W2064675550","https://openalex.org/W2118463056","https://openalex.org/W2207044458","https://openalex.org/W2413794162","https://openalex.org/W2415204069","https://openalex.org/W2475334473","https://openalex.org/W2604662567","https://openalex.org/W2608787653","https://openalex.org/W2723293840","https://openalex.org/W2808571346","https://openalex.org/W2896457183","https://openalex.org/W2962739339","https://openalex.org/W2962958286","https://openalex.org/W2963351448","https://openalex.org/W2963973721","https://openalex.org/W2970641574","https://openalex.org/W2983762620","https://openalex.org/W3012439218","https://openalex.org/W3026103636","https://openalex.org/W3041006851","https://openalex.org/W3092479965","https://openalex.org/W4385245566","https://openalex.org/W4396952261","https://openalex.org/W6631190155","https://openalex.org/W6636510571","https://openalex.org/W6686207219","https://openalex.org/W6715743342","https://openalex.org/W6739901393","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W2350741829","https://openalex.org/W2530322880","https://openalex.org/W1596801655"],"abstract_inverted_index":{"In":[0,87],"nowadays,":[1],"the":[2,15,42,45,70,82,109,140,146,151,155,174,189,193,200],"large-scale":[3],"e-commerce":[4,26],"corporations":[5],"tend":[6],"to":[7,13,30,78,89,122,167,187,208],"operate":[8],"their":[9],"own":[10],"logistics":[11,38],"networks":[12],"guarantee":[14],"speed,":[16],"safety":[17],"and":[18,36,60,72,81,184],"economic":[19],"efficiency":[20],"of":[21,63,84,111,158],"goods":[22,58,71,104,141],"delivery.":[23],"Thus,":[24],"an":[25,32,93],"corporation":[27],"usually":[28],"needs":[29],"manage":[31],"online":[33],"retailing":[34],"platform":[35,39],"a":[37,132,164,169],"simultaneously.":[40],"Despite":[41],"offered":[43],"convenience,":[44],"cross-platform":[46],"management":[47],"faces":[48],"grand":[49],"challenges":[50],"on":[51,138],"security.":[52],"The":[53],"inappropriate":[54],"philosophies":[55],"for":[56,103,135],"maintaining":[57],"information":[59,105,142],"malicious":[61],"behaviors":[62],"some":[64],"merchants":[65],"may":[66],"induce":[67],"mismatch":[68],"between":[69],"corresponding":[73],"information,":[74],"which":[75,127],"consequently":[76],"leads":[77],"incorrect":[79],"delivery":[80],"degradation":[83],"customer":[85],"experience.":[86],"order":[88],"tackle":[90],"this":[91,101],"issue,":[92],"innovative":[94],"model":[95],"fusion":[96],"method":[97,153,176],"is":[98,143,177,185],"proposed":[99,152,175],"in":[100],"work":[102],"inspection.":[106],"It":[107],"investigates":[108],"advantages":[110],"multiple":[112],"natural":[113],"language":[114],"processing":[115],"models":[116],"as":[117,119],"well":[118],"domain":[120],"knowledge":[121],"extract":[123],"informative":[124],"text":[125],"features,":[126],"are":[128],"subsequently":[129],"fed":[130],"into":[131],"multi-layer":[133],"perceptron":[134],"final":[136],"decision":[137],"whether":[139],"accurate.":[144],"Unlike":[145],"recent":[147],"popular":[148],"deep":[149],"architectures,":[150],"leverages":[154],"complimentary":[156,201],"effect":[157],"features":[159],"from":[160],"different":[161],"sources":[162],"utilizing":[163],"wide":[165],"structure":[166],"achieve":[168],"superior":[170],"inspection":[171],"accuracy.":[172],"Finally,":[173],"validated":[178],"using":[179],"real":[180],"JD":[181],"Logistics":[182],"data":[183],"demonstrated":[186],"outperform":[188],"existing":[190],"techniques.":[191],"Furthermore,":[192],"experimental":[194],"results":[195],"also":[196],"demonstrate":[197],"that":[198],"leveraging":[199],"effects":[202],"can":[203],"bring":[204],"additional":[205],"improvement":[206],"compared":[207],"merely":[209],"exploring":[210],"deeper.":[211]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}