{"id":"https://openalex.org/W3096507354","doi":"https://doi.org/10.1109/tnnls.2020.3028572","title":"IPGAN: Generating Informative Item Pairs by Adversarial Sampling","display_name":"IPGAN: Generating Informative Item Pairs by Adversarial Sampling","publication_year":2020,"publication_date":"2020-10-27","ids":{"openalex":"https://openalex.org/W3096507354","doi":"https://doi.org/10.1109/tnnls.2020.3028572","mag":"3096507354","pmid":"https://pubmed.ncbi.nlm.nih.gov/33108294"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.3028572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3028572","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5007061198","display_name":"Guibing Guo","orcid":"https://orcid.org/0000-0002-1709-5056"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guibing Guo","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-1709-5056","affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101911637","display_name":"Huan Zhou","orcid":"https://orcid.org/0000-0002-8251-8158"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Zhou","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-8251-8158","affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100679034","display_name":"Bowei Chen","orcid":"https://orcid.org/0000-0002-2225-8796"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowei Chen","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-2225-8796","affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119269917","display_name":"Zhirong Liu","orcid":"https://orcid.org/0000-0002-1893-312X"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhirong Liu","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab, Shenzhen, China","Huawei Noah's Ark Lab, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]},{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319784","display_name":"Xu Xiao\ue00b","orcid":"https://orcid.org/0000-0001-5774-1094"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Xu","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0001-5774-1094","affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101755392","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0003-0144-1775"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["Department of Computer Science, University College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0003-0144-1775","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University College London, London, U.K","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021124418","display_name":"Zhenhua Dong","orcid":"https://orcid.org/0000-0002-2231-4663"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Dong","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab, Shenzhen, China","Huawei Noah's Ark Lab, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]},{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083350101","display_name":"Xiuqiang He","orcid":"https://orcid.org/0000-0002-4115-8205"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuqiang He","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab, Shenzhen, China","Huawei Noah's Ark Lab, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]},{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5007061198"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":2.7842,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.92521002,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"33","issue":"2","first_page":"694","last_page":"706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9901999831199646,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7016104459762573},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6901350021362305},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6276693344116211},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5794301629066467},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5560601353645325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5478605031967163},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4794287085533142},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.44764137268066406},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4447498917579651},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41564705967903137}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7016104459762573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6901350021362305},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6276693344116211},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5794301629066467},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5560601353645325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478605031967163},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4794287085533142},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.44764137268066406},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4447498917579651},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41564705967903137},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2020.3028572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3028572","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:33108294","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33108294","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3062465163","display_name":null,"funder_award_id":"61972078","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4591949316","display_name":null,"funder_award_id":"N181705007","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8828627166","display_name":null,"funder_award_id":"61702084","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1690919088","https://openalex.org/W1976999215","https://openalex.org/W1991055526","https://openalex.org/W1994389483","https://openalex.org/W2074290495","https://openalex.org/W2102035799","https://openalex.org/W2415326922","https://openalex.org/W2467216808","https://openalex.org/W2470901364","https://openalex.org/W2507427036","https://openalex.org/W2520779888","https://openalex.org/W2539247542","https://openalex.org/W2605350416","https://openalex.org/W2612290335","https://openalex.org/W2619206542","https://openalex.org/W2640408555","https://openalex.org/W2767778908","https://openalex.org/W2788456731","https://openalex.org/W2792285786","https://openalex.org/W2798746280","https://openalex.org/W2798868970","https://openalex.org/W2808246249","https://openalex.org/W2912967843","https://openalex.org/W2963169753","https://openalex.org/W2964268978","https://openalex.org/W2965021023","https://openalex.org/W2966799427","https://openalex.org/W3101023724","https://openalex.org/W6600827882","https://openalex.org/W6680830989","https://openalex.org/W6732248266"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W2482350142","https://openalex.org/W2965546495","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W2042102171","https://openalex.org/W4251223544"],"abstract_inverted_index":{"Negative":[0],"sampling":[1,13,92,148],"plays":[2],"an":[3,138],"important":[4],"role":[5],"in":[6,152,242],"ranking-based":[7],"recommender":[8],"models.":[9],"However,":[10],"most":[11],"existing":[12],"methods":[14],"cannot":[15],"generate":[16],"informative":[17,96,174],"item":[18,97,139,171,198],"pairs":[19,172],"with":[20,130,221],"positive":[21,36,43,68,83,104,133,157],"and":[22,51,59,69,158,197],"negative":[23,70,73,124,159],"instances":[24],"due":[25],"to":[26,63,94,176,192],"two":[27,153],"limitations:":[28],"1)":[29],"they":[30,61],"merely":[31],"treat":[32],"observed":[33,55,117],"items":[34,44,47,58,71,109],"as":[35],"instances,":[37,160],"ignoring":[38],"the":[39,52,65,78,108,112,131,169,177,202,215],"existence":[40],"of":[41,54,81,115,217,244],"potential":[42,82],"(i.e.,":[45],"nonobserved":[46],"users":[48],"may":[49,76],"prefer)":[50],"probability":[53],"but":[56],"noisy":[57],"2)":[60],"fail":[62],"capture":[64],"relationship":[66],"between":[67],"during":[72],"sampling,":[74],"which":[75],"cause":[77],"unexpected":[79],"selection":[80],"items.":[84,118],"In":[85,162],"this":[86],"article,":[87],"we":[88,100,120,136,187],"introduce":[89],"a":[90,103,123,181,189],"dynamic":[91],"strategy":[93,149],"search":[95],"pairs.":[98],"Specifically,":[99],"first":[101],"sample":[102],"instance":[105,125],"from":[106,206],"all":[107],"by":[110,126,180,200],"leveraging":[111],"overall":[113],"features":[114],"user's":[116],"Then,":[119],"strategically":[121],"select":[122],"considering":[127],"its":[128],"correlation":[129],"sampled":[132,170],"one.":[134],"Formally,":[135],"propose":[137,188],"pair":[140],"generative":[141,154],"adversarial":[142],"network":[143],"named":[144],"IPGAN,":[145],"where":[146],"our":[147,236],"is":[150,185],"realized":[151],"models":[155],"for":[156,225],"respectively.":[161],"addition,":[163],"IPGAN":[164],"can":[165,211],"also":[166,212],"ensure":[167],"that":[168,235],"are":[173],"relative":[175],"ground":[178],"truth":[179],"discriminative":[182],"model.":[183],"What":[184],"more,":[186],"batch-training":[190],"approach":[191,210,237],"further":[193],"enhance":[194],"both":[195],"user":[196],"modeling":[199],"alleviating":[201],"special":[203],"bias":[204],"(noise)":[205],"different":[207],"users.":[208],"This":[209],"significantly":[213],"accelerate":[214],"process":[216],"model":[218],"training":[219],"compared":[220],"classical":[222],"GAN":[223],"method":[224],"recommendation.":[226],"Experimental":[227],"results":[228],"on":[229],"three":[230],"real":[231],"data":[232],"sets":[233],"show":[234],"outperforms":[238],"other":[239],"state-of-the-art":[240],"approaches":[241],"terms":[243],"recommendation":[245],"accuracy.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-12T08:28:47.272897","created_date":"2025-10-10T00:00:00"}