{"id":"https://openalex.org/W4396843716","doi":"https://doi.org/10.1145/3589335.3648302","title":"A Semi-supervised Multi-channel Graph Convolutional Network for Query Classification in E-commerce","display_name":"A Semi-supervised Multi-channel Graph Convolutional Network for Query Classification in E-commerce","publication_year":2024,"publication_date":"2024-05-12","ids":{"openalex":"https://openalex.org/W4396843716","doi":"https://doi.org/10.1145/3589335.3648302"},"language":"en","primary_location":{"id":"doi:10.1145/3589335.3648302","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3648302","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3648302","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3648302","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026726435","display_name":"Chunyuan Yuan","orcid":"https://orcid.org/0000-0001-9794-5032"},"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":true,"raw_author_name":"Chunyuan Yuan","raw_affiliation_strings":["JD.com, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD.com, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102011859","display_name":"Ming Pang","orcid":"https://orcid.org/0000-0003-0454-0808"},"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":"Ming Pang","raw_affiliation_strings":["JD.com, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD.com, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082003513","display_name":"Zheng Fang","orcid":"https://orcid.org/0000-0001-6691-0312"},"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":"Zheng Fang","raw_affiliation_strings":["JD.com, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD.com, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069417501","display_name":"Xue Jiang","orcid":"https://orcid.org/0000-0001-6944-9031"},"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":"Xue Jiang","raw_affiliation_strings":["JD.com, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD.com, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070986387","display_name":"Changping Peng","orcid":"https://orcid.org/0009-0002-2561-1919"},"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":"Changping Peng","raw_affiliation_strings":["JD.com, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD.com, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009831083","display_name":"Zhangang Lin","orcid":"https://orcid.org/0000-0003-1379-5044"},"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":"Zhangang Lin","raw_affiliation_strings":["JD.com, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD.com, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5026726435"],"corresponding_institution_ids":["https://openalex.org/I4210103986"],"apc_list":null,"apc_paid":null,"fwci":4.8464,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.95114809,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"56","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9979000091552734,"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":0.9979000091552734,"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":0.8326411247253418},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5382549166679382},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3586607873439789},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.349321573972702},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2553119659423828}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8326411247253418},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5382549166679382},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3586607873439789},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.349321573972702},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2553119659423828}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589335.3648302","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3648302","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3648302","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589335.3648302","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3648302","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3648302","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396843716.pdf"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1484330506","https://openalex.org/W1953606363","https://openalex.org/W2035055162","https://openalex.org/W2141880913","https://openalex.org/W2163375626","https://openalex.org/W2593390416","https://openalex.org/W2739996966","https://openalex.org/W2901069632","https://openalex.org/W2962893388","https://openalex.org/W2963912736","https://openalex.org/W2971092323","https://openalex.org/W2989224055","https://openalex.org/W2997985889","https://openalex.org/W3035690777","https://openalex.org/W3117408577","https://openalex.org/W4361231059"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Query":[0],"intent":[1,21,87],"classification":[2,22],"is":[3,66,122],"an":[4,141],"essential":[5],"module":[6],"for":[7,68,88,124],"customers":[8],"to":[9,34,48,73,84,112,136,140,161,205],"quickly":[10],"find":[11],"desired":[12],"products":[13,69,89],"on":[14,25,43],"the":[15,26,55,81,97,113,116,119,125,132,137,163,167,181,186,190,197,207,213,228,236],"e-commerce":[16],"application.":[17],"Most":[18],"existing":[19],"query":[20,126,191],"methods":[23,40],"rely":[24],"users'":[27,86],"click":[28,59],"behavior":[29],"as":[30],"a":[31,106,153],"supervised":[32],"signal":[33],"construct":[35],"training":[36],"samples.":[37,60],"However,":[38],"these":[39],"based":[41],"entirely":[42],"posterior":[44,120,182,216],"labels":[45,210],"may":[46],"lead":[47],"serious":[49],"category":[50,177],"imbalance":[51],"problems":[52,165],"because":[53],"of":[54,115,146,169,203,215],"Matthew":[56],"effect":[57],"in":[58,94],"Compared":[61],"with":[62,127],"popular":[63],"categories,":[64],"it":[65,195],"difficult":[67],"under":[70,90],"long-tail":[71,91,100],"categories":[72,101,204],"obtain":[74,103],"traffic":[75],"and":[76,143,172,179,192,199,211,223,227,243],"user":[77],"clicks,":[78],"which":[79,130,239],"makes":[80,131],"models":[82],"unable":[83],"detect":[85],"categories.":[92,147,193],"This":[93],"turn":[95],"aggravates":[96],"problem":[98],"that":[99,232],"cannot":[102],"traffic,":[104],"forming":[105],"vicious":[107],"circle.":[108],"In":[109,148],"addition,":[110],"due":[111],"randomness":[114],"user's":[117],"click,":[118],"label":[121,170,183,217],"unstable":[123,142],"similar":[128],"semantics,":[129],"model":[133],"very":[134],"sensitive":[135],"input,":[138],"leading":[139],"incomplete":[144],"recall":[145],"this":[149],"paper,":[150],"we":[151],"propose":[152],"novel":[154],"Semi-supervised":[155],"Multi-channel":[156],"Graph":[157],"Convolutional":[158],"Network":[159],"(SMGCN)":[160],"address":[162],"above":[164],"from":[166],"perspective":[168],"association":[171],"semi-supervised":[173],"learning.":[174],"SMGCN":[175,233],"extends":[176],"information":[178],"enhances":[180],"by":[184],"utilizing":[185],"similarity":[187,201],"score":[188],"between":[189],"Furthermore,":[194],"leverages":[196],"co-occurrence":[198],"semantic":[200],"graph":[202],"strengthen":[206],"relations":[208],"among":[209],"weaken":[212],"influence":[214],"instability.":[218],"We":[219],"conduct":[220],"extensive":[221],"offline":[222],"online":[224],"A/B":[225],"experiments,":[226],"experimental":[229],"results":[230],"show":[231],"significantly":[234],"outperforms":[235],"strong":[237],"baselines,":[238],"shows":[240],"its":[241],"effectiveness":[242],"practicality.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-01T08:55:55.761014","created_date":"2025-10-10T00:00:00"}