{"id":"https://openalex.org/W4291125090","doi":"https://doi.org/10.1145/3534678.3539191","title":"A Graph Learning Based Framework for Billion-Scale Offline User Identification","display_name":"A Graph Learning Based Framework for Billion-Scale Offline User Identification","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4291125090","doi":"https://doi.org/10.1145/3534678.3539191"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539191","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539191","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5008647105","display_name":"Daixin Wang","orcid":"https://orcid.org/0000-0002-5166-0362"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Daixin Wang","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063557450","display_name":"Zujian Weng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zujian Weng","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002031940","display_name":"Zhengwei Wu","orcid":"https://orcid.org/0000-0002-3500-5990"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhengwei Wu","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050079548","display_name":"Zhiqiang Zhang","orcid":"https://orcid.org/0000-0003-0204-3867"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiqiang Zhang","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009228005","display_name":"Peng Cui","orcid":"https://orcid.org/0000-0003-2957-8511"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Cui","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102013365","display_name":"Hongwei Zhao","orcid":"https://orcid.org/0000-0002-2977-9746"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongwei Zhao","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045140292","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-6033-6102"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5008647105"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.06,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.25552545,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"4001","last_page":"4009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11644","display_name":"Spam and Phishing Detection","score":0.9897000193595886,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9872999787330627,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6973960399627686},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.45145663619041443},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4243260324001312},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37125682830810547},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33849769830703735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3345023989677429},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3344005346298218}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6973960399627686},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.45145663619041443},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4243260324001312},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37125682830810547},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33849769830703735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3345023989677429},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3344005346298218},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539191","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539191","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7972761409","display_name":null,"funder_award_id":"U1936219","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2124509324","https://openalex.org/W2151103935","https://openalex.org/W2154851992","https://openalex.org/W2163808566","https://openalex.org/W2165731615","https://openalex.org/W2187089797","https://openalex.org/W2295598076","https://openalex.org/W2325939864","https://openalex.org/W2393319904","https://openalex.org/W2475334473","https://openalex.org/W2594407953","https://openalex.org/W2609575245","https://openalex.org/W2784163702","https://openalex.org/W2911286998","https://openalex.org/W2932399282","https://openalex.org/W2962756421","https://openalex.org/W2963415211","https://openalex.org/W2963656735","https://openalex.org/W2963839617","https://openalex.org/W2970632477","https://openalex.org/W2981574046","https://openalex.org/W2982112268","https://openalex.org/W3004349648","https://openalex.org/W3004507689","https://openalex.org/W3009901425","https://openalex.org/W3035096461","https://openalex.org/W3094473713","https://openalex.org/W3099064659","https://openalex.org/W3101227480","https://openalex.org/W3103152812","https://openalex.org/W3103513278","https://openalex.org/W3104097132","https://openalex.org/W3111208380","https://openalex.org/W3175998650","https://openalex.org/W3197032092","https://openalex.org/W4213082449"],"related_works":["https://openalex.org/W4226370857","https://openalex.org/W3205049642","https://openalex.org/W3023484842","https://openalex.org/W1524858705","https://openalex.org/W4221147382","https://openalex.org/W3029957763","https://openalex.org/W2907467702","https://openalex.org/W2923818335","https://openalex.org/W4226126822","https://openalex.org/W4226361842"],"abstract_inverted_index":{"Offline":[0],"user":[1,54],"identification":[2,14,47,55],"is":[3,56],"a":[4,36,43,94,103],"scenario":[5],"that":[6],"users":[7,64,112],"use":[8,60],"their":[9],"bio-information":[10],"like":[11],"faces":[12,61],"as":[13,27,84],"in":[15,22,29,32,38,89,106],"offline":[16,24,39,53,90],"venues,":[17],"which":[18],"has":[19],"been":[20],"applied":[21],"many":[23],"scenarios":[25,59],"such":[26,42,83],"verification":[28],"banks,":[30],"check-in":[31],"hotels":[33],"and":[34,65,74,87,117],"making":[35],"purchase":[37],"merchants.":[40],"In":[41],"scenario,":[44],"designing":[45],"an":[46],"approach":[48],"to":[49,62,79,101],"do":[50],"extremely":[51],"accurate":[52],"critical.":[57],"Most":[58],"identify":[63],"previous":[66],"algorithms":[67,100],"are":[68],"mainly":[69],"based":[70],"on":[71],"visual":[72],"features":[73],"computer-vision":[75,99],"models.":[76],"However,":[77],"due":[78],"the":[80,121],"large":[81],"variations":[82],"pose,":[85],"illumination":[86],"occlusions":[88],"scenarios,":[91],"it":[92],"remains":[93],"challenging":[95],"problem":[96],"for":[97,120],"existing":[98],"get":[102],"satisfying":[104],"accuracy":[105,119],"real-world":[107],"scenarios.":[108],"Furthermore,":[109],"billion-scale":[110],"candidate":[111],"also":[113],"require":[114],"high":[115,118],"efficiency":[116],"approach.":[122]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}