{"id":"https://openalex.org/W2592375611","doi":"https://doi.org/10.24963/ijcai.2017/6","title":"Diverse Weighted Bipartite b-Matching","display_name":"Diverse Weighted Bipartite b-Matching","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2592375611","doi":"https://doi.org/10.24963/ijcai.2017/6","mag":"2592375611"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/6","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/6","pdf_url":"https://www.ijcai.org/proceedings/2017/0006.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0006.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040705509","display_name":"Faez Ahmed","orcid":"https://orcid.org/0000-0002-5227-2628"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Faez Ahmed","raw_affiliation_strings":["Department of Mechanical Engineering, University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071538560","display_name":"John P. Dickerson","orcid":"https://orcid.org/0000-0003-2231-680X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John P. Dickerson","raw_affiliation_strings":["Computer Science Department, University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036788329","display_name":"Mark Fuge","orcid":"https://orcid.org/0000-0003-3819-8895"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Fuge","raw_affiliation_strings":["Department of Mechanical Engineering, University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":4.5674,"has_fulltext":true,"cited_by_count":51,"citation_normalized_percentile":{"value":0.95661298,"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":"35","last_page":"41"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","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"}},"topics":[{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","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"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9955000281333923,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.995199978351593,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.8296276330947876},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6369826793670654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5215684771537781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3942911624908447},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3444923460483551},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30539441108703613},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.17929819226264954},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1362151801586151},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.069487065076828}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.8296276330947876},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6369826793670654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5215684771537781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3942911624908447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3444923460483551},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30539441108703613},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.17929819226264954},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1362151801586151},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.069487065076828}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2017/6","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/6","pdf_url":"https://www.ijcai.org/proceedings/2017/0006.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1702.07134","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1702.07134","pdf_url":"https://arxiv.org/pdf/1702.07134","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/6","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/6","pdf_url":"https://www.ijcai.org/proceedings/2017/0006.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2592375611.pdf","grobid_xml":"https://content.openalex.org/works/W2592375611.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1680189815","https://openalex.org/W1990184998","https://openalex.org/W1996768744","https://openalex.org/W2034464625","https://openalex.org/W2057175746","https://openalex.org/W2062340319","https://openalex.org/W2088677683","https://openalex.org/W2126184790","https://openalex.org/W2138779671","https://openalex.org/W2144933361","https://openalex.org/W2144998676","https://openalex.org/W2145562323","https://openalex.org/W2153578526","https://openalex.org/W2155203104","https://openalex.org/W2155314350","https://openalex.org/W2219888463","https://openalex.org/W2225560834","https://openalex.org/W2286300105","https://openalex.org/W2288846112","https://openalex.org/W2293140664","https://openalex.org/W2295492017","https://openalex.org/W2342411541","https://openalex.org/W2400255467","https://openalex.org/W2508625104","https://openalex.org/W2576271642","https://openalex.org/W2616515875","https://openalex.org/W2949989304","https://openalex.org/W3122196295","https://openalex.org/W6666006430","https://openalex.org/W6791858558","https://openalex.org/W6863994431"],"related_works":["https://openalex.org/W2567825307","https://openalex.org/W1592682627","https://openalex.org/W4295762832","https://openalex.org/W2945016732","https://openalex.org/W2785998768","https://openalex.org/W2371352078","https://openalex.org/W2362975861","https://openalex.org/W2804963084","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Bipartite":[0],"matching,":[1],"where":[2,98],"agents":[3,13,99,112],"on":[4,16,100,113,189],"one":[5,101],"side":[6,102],"of":[7,80,95,103,111,120,123,144,163,167,186,198],"a":[8,20,46,87,93,117,124,128,134,150,165,177],"market":[9,105],"are":[10],"matched":[11,108],"to":[12,44,53,61,109,132,172],"or":[14],"items":[15],"the":[17,78,104,114,121,145,161,168,184,196],"other,":[18],"is":[19,42,200,207],"classical":[21,118],"problem":[22,137],"in":[23,31,72,203],"computer":[24],"science":[25],"and":[26,35,70,75,91,141,175,193],"economics,":[27],"with":[28,154],"widespread":[29],"application":[30],"healthcare,":[32],"education,":[33],"advertising,":[34],"general":[36],"resource":[37],"allocation.":[38],"A":[39,63],"practitioner's":[40],"goal":[41],"typically":[43],"maximize":[45],"matching":[47,73,97],"market's":[48],"economic":[49],"efficiency,":[50],"possibly":[51],"subject":[52,79],"some":[54],"fairness":[55,69],"requirements":[56],"that":[57,138,195],"promote":[58],"equal":[59],"access":[60],"resources.":[62],"natural":[64],"balancing":[65],"act":[66],"exists":[67],"between":[68],"efficiency":[71,169],"markets,":[74],"has":[76],"been":[77],"much":[81],"research.In":[82],"this":[83],"paper,":[84],"we":[85,126,182],"study":[86],"complementary":[88],"goal---balancing":[89],"diversity":[90,122,140,199],"efficiency---in":[92],"generalization":[94],"bipartite":[96],"can":[106],"be":[107],"sets":[110],"other.":[115],"Adapting":[116],"definition":[119],"set,":[125],"propose":[127],"quadratic":[129],"programming-based":[130],"approach":[131],"solving":[133],"submodular":[135],"minimization":[136],"balances":[139],"total":[142],"weight":[143],"solution.":[146],"We":[147,158],"also":[148],"provide":[149],"scalable":[151],"greedy":[152],"algorithm":[153],"theoretical":[155,179],"performance":[156],"bounds.":[157],"then":[159],"define":[160],"price":[162,197],"diversity,":[164,174],"measure":[166],"loss":[170],"due":[171],"enforcing":[173],"give":[176],"worst-case":[178],"bound.":[180],"Finally,":[181],"demonstrate":[183],"efficacy":[185],"our":[187],"methods":[188],"three":[190],"real-world":[191],"datasets,":[192],"show":[194],"not":[201],"bad":[202],"practice.":[204],"Our":[205],"code":[206],"publicly":[208],"accessible":[209],"for":[210],"further":[211],"research.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}