{"id":"https://openalex.org/W2963766505","doi":"https://doi.org/10.1145/3209978.3210184","title":"Generative Adversarial Nets for Information Retrieval","display_name":"Generative Adversarial Nets for Information Retrieval","publication_year":2018,"publication_date":"2018-06-27","ids":{"openalex":"https://openalex.org/W2963766505","doi":"https://doi.org/10.1145/3209978.3210184","mag":"2963766505"},"language":"en","primary_location":{"id":"doi:10.1145/3209978.3210184","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3209978.3210184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval","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/A5090720315","display_name":"Weinan Zhang","orcid":"https://orcid.org/0000-0002-0127-2425"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weinan Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5090720315"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.7312,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.77778792,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1375","last_page":"1378"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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":0.8445366621017456},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.7280377745628357},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6302881240844727},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.620838463306427},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.48118168115615845},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4756823778152466},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47001078724861145},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.424391508102417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40568602085113525},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4056243896484375},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3700508773326874},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33291947841644287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8445366621017456},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.7280377745628357},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6302881240844727},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.620838463306427},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.48118168115615845},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4756823778152466},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47001078724861145},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.424391508102417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40568602085113525},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4056243896484375},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3700508773326874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33291947841644287},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3209978.3210184","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3209978.3210184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G3256823474","display_name":null,"funder_award_id":"61702327","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":26,"referenced_works":["https://openalex.org/W648786980","https://openalex.org/W1972594981","https://openalex.org/W2093390569","https://openalex.org/W2119717200","https://openalex.org/W2143331230","https://openalex.org/W2149427297","https://openalex.org/W2155027007","https://openalex.org/W2186845332","https://openalex.org/W2512971201","https://openalex.org/W2536015822","https://openalex.org/W2547875792","https://openalex.org/W2565378226","https://openalex.org/W2605350416","https://openalex.org/W2616969219","https://openalex.org/W2619206542","https://openalex.org/W2765422230","https://openalex.org/W2768532803","https://openalex.org/W2768762802","https://openalex.org/W2907069037","https://openalex.org/W2919115771","https://openalex.org/W2963456134","https://openalex.org/W2963672682","https://openalex.org/W2963924289","https://openalex.org/W2964268978","https://openalex.org/W3101023724","https://openalex.org/W4206765718"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W4396941953","https://openalex.org/W2987280934"],"abstract_inverted_index":{"Generative":[0],"adversarial":[1,20],"nets":[2],"(GANs)":[3],"have":[4],"been":[5],"widely":[6],"studied":[7],"during":[8],"the":[9,32,39,42,82,100,104,118,131,145,156,166,178,185,203],"recent":[10,187],"development":[11],"of":[12,41,120,149,168,235],"deep":[13],"learning":[14],"and":[15,91,103,123,155,177,210,232],"unsupervised":[16],"learning.":[17],"With":[18],"an":[19],"training":[21],"mechanism,":[22],"GAN":[23,101,121,136,147,180],"manages":[24],"to":[25,30,73,77,134,212],"train":[26],"a":[27,47,55,229,233],"generative":[28],"model":[29,44],"fit":[31],"underlying":[33],"unknown":[34],"real":[35,51],"data":[36,48,63,83,108,139,153,171,191],"distribution":[37,64,154],"under":[38],"guidance":[40],"discriminative":[43],"estimating":[45],"whether":[46],"instance":[49],"is":[50,57,70,84],"or":[52],"generated.":[53],"Such":[54],"framework":[56,122,148],"originally":[58],"proposed":[59],"for":[60,239],"fitting":[61,109,150,192],"continuous":[62],"such":[65,87,207],"as":[66,88,208],"images,":[67],"thus":[68],"it":[69],"not":[71],"straightforward":[72],"be":[74],"directly":[75],"applied":[76],"information":[78,112,160,221,242],"retrieval":[79,113],"scenarios":[80],"where":[81],"mostly":[85],"discrete,":[86],"IDs,":[89],"text":[90,175],"graphs.":[92],"In":[93],"this":[94,226],"tutorial,":[95],"we":[96,128,142,163,183,200,224],"focus":[97],"on":[98,106,159,189,218],"discussing":[99],"techniques":[102,196],"variants":[105],"discrete":[107,138,170],"in":[110,220,241],"various":[111],"scenarios.":[114],"(i)":[115],"We":[116],"introduce":[117,143,202],"fundamentals":[119],"its":[124],"theoretic":[125],"properties;":[126],"(ii)":[127],"carefully":[129],"study":[130],"promising":[132],"solutions":[133],"extend":[135],"onto":[137],"generation;":[140],"(iii)":[141],"IRGAN,":[144],"fundamental":[146],"single":[151],"ID":[152],"direct":[157],"application":[158],"retrieval;":[161],"(iv)":[162],"further":[164,236],"discuss":[165],"task":[167],"sequential":[169],"generation":[172],"tasks,":[173],"e.g.,":[174],"generation,":[176],"corresponding":[179],"solutions;":[181],"(v)":[182],"present":[184],"most":[186],"work":[188],"graph/network":[190],"with":[193,228],"node":[194],"embedding":[195],"by":[197],"GANs.":[198],"Meanwhile,":[199],"also":[201],"relevant":[204],"open-source":[205],"platforms":[206],"IRGAN":[209],"Texygen":[211],"help":[213],"audience":[214],"conduct":[215],"research":[216,237],"experiments":[217],"GANs":[219,240],"retrieval.":[222,243],"Finally,":[223],"conclude":[225],"tutorial":[227],"comprehensive":[230],"summarization":[231],"prospect":[234],"directions":[238]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}