{"id":"https://openalex.org/W4226104444","doi":"https://doi.org/10.1109/access.2022.3151640","title":"Reviewer Recommendations Using Document Vector Embeddings and a Publisher Database: Implementation and Evaluation","display_name":"Reviewer Recommendations Using Document Vector Embeddings and a Publisher Database: Implementation and Evaluation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226104444","doi":"https://doi.org/10.1109/access.2022.3151640"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3151640","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3151640","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09714338.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09714338.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078866075","display_name":"Yue Zhao","orcid":"https://orcid.org/0000-0002-0819-5012"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yue Zhao","raw_affiliation_strings":["Rochester Data Science Consortium, Rochester, NY, USA"],"affiliations":[{"raw_affiliation_string":"Rochester Data Science Consortium, Rochester, NY, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078900695","display_name":"Ajay Anand","orcid":"https://orcid.org/0000-0002-4230-8981"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ajay Anand","raw_affiliation_strings":["Goergen Institute for Data Science, University of Rochester, Rochester, NY, USA"],"affiliations":[{"raw_affiliation_string":"Goergen Institute for Data Science, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100705959","display_name":"Gaurav Sharma","orcid":"https://orcid.org/0000-0001-9735-9519"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gaurav Sharma","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078866075"],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.9093,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8842488,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"10","issue":null,"first_page":"21798","last_page":"21811"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","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/T13274","display_name":"Expert finding and Q&A systems","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/T10028","display_name":"Topic Modeling","score":0.9918000102043152,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9642000198364258,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.7798194885253906},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6745022535324097},{"id":"https://openalex.org/keywords/listing","display_name":"Listing (finance)","score":0.6286914944648743},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.606429934501648},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5165247321128845},{"id":"https://openalex.org/keywords/paragraph","display_name":"Paragraph","score":0.5095503330230713},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4198874235153198},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.3511013984680176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3177040219306946},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2555166780948639},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0926923155784607},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07742756605148315}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7798194885253906},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6745022535324097},{"id":"https://openalex.org/C2779820595","wikidata":"https://www.wikidata.org/wiki/Q798505","display_name":"Listing (finance)","level":2,"score":0.6286914944648743},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.606429934501648},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5165247321128845},{"id":"https://openalex.org/C2777206241","wikidata":"https://www.wikidata.org/wiki/Q194431","display_name":"Paragraph","level":2,"score":0.5095503330230713},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4198874235153198},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3511013984680176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3177040219306946},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2555166780948639},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0926923155784607},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07742756605148315},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3151640","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3151640","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09714338.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b6e5241d40d044439807cb63387b871f","is_oa":true,"landing_page_url":"https://doaj.org/article/b6e5241d40d044439807cb63387b871f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 21798-21811 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3151640","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3151640","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09714338.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1840908629","display_name":null,"funder_award_id":"CCF-193496","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G29977575","display_name":null,"funder_award_id":"1934962","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5381891446","display_name":null,"funder_award_id":"CCF-1934962","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320310246","display_name":"University of Rochester","ror":"https://ror.org/022kthw22"},{"id":"https://openalex.org/F4320310728","display_name":"Centre International de Recherche sur le Cancer","ror":"https://ror.org/00v452281"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4226104444.pdf","grobid_xml":"https://content.openalex.org/works/W4226104444.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W168564468","https://openalex.org/W295894637","https://openalex.org/W941230081","https://openalex.org/W1614298861","https://openalex.org/W2048910496","https://openalex.org/W2124002218","https://openalex.org/W2126793736","https://openalex.org/W2131571251","https://openalex.org/W2166001595","https://openalex.org/W2325227998","https://openalex.org/W2524358665","https://openalex.org/W2526355008","https://openalex.org/W2735784619","https://openalex.org/W2753788081","https://openalex.org/W2908436998","https://openalex.org/W2946830487","https://openalex.org/W2963514026","https://openalex.org/W4213009331","https://openalex.org/W4231510805","https://openalex.org/W4244411353","https://openalex.org/W6610517080","https://openalex.org/W6624664881","https://openalex.org/W6636510571","https://openalex.org/W6639619044","https://openalex.org/W6679713772","https://openalex.org/W6682947546"],"related_works":["https://openalex.org/W2377059580","https://openalex.org/W4200355488","https://openalex.org/W3215892509","https://openalex.org/W2928616779","https://openalex.org/W2412592434","https://openalex.org/W2010523086","https://openalex.org/W4244602709","https://openalex.org/W594987446","https://openalex.org/W2012131063","https://openalex.org/W2528358464"],"abstract_inverted_index":{"We":[0,161],"develop":[1],"and":[2,24,63,80,91,152,172,179,195,244],"evaluate":[3],"an":[4,76],"automated":[5],"data-driven":[6],"framework":[7],"for":[8,12,22,100,156,203,214],"providing":[9],"reviewer":[10,147,192],"recommendations":[11,224],"submitted":[13],"manuscripts.":[14],"Given":[15],"inputs":[16],"comprising":[17],"a":[18,25,28,36,48,81,94,143,164,188],"set":[19],"of":[20,27,30,70,75,97,111,139,222],"manuscripts":[21,141],"review":[23],"listing":[26],"pool":[29],"prospective":[31],"reviewers,":[32],"our":[33],"system":[34,106,210],"uses":[35,107],"publisher":[37,144],"database":[38,145],"to":[39,65,86,92],"extract":[40],"papers":[41,79],"authored":[42],"by":[43],"the":[44,112,131,154,184,215,223],"reviewers":[45,99],"from":[46,142],"which":[47,115,128],"<italic":[49,54,226,233,239,248],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[50,55,227,234,240,249],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Paragraph":[51],"Vector</i>":[52],"(":[53],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">doc2vec</i>":[56],")":[57],"neural":[58],"network":[59],"model":[60],"is":[61,211],"learned":[62],"used":[64,85],"obtain":[66],"vector":[67],"space":[68],"embeddings":[69,74],"documents.":[71],"Similarities":[72],"between":[73],"individual":[77],"reviewer\u2019s":[78,140],"manuscript":[82],"are":[83],"then":[84],"compute":[87],"manuscript-reviewer":[88],"match":[89],"scores":[90],"generate":[93],"ranked":[95],"list":[96],"recommended":[98],"each":[101],"manuscript.":[102],"Our":[103,209],"mainline":[104,216],"proposed":[105],"full":[108],"text":[109],"versions":[110],"reviewers\u2019":[113],"papers,":[114],"we":[116,198],"demonstrate":[117],"performs":[118],"significantly":[119],"better":[120],"than":[121],"models":[122],"developed":[123],"based":[124],"on":[125,180],"abstracts":[126],"alone,":[127],"has":[129],"been":[130],"predominant":[132],"paradigm":[133],"in":[134,206],"prior":[135,181],"work.":[136],"Direct":[137],"retrieval":[138],"reduces":[146],"burden,":[148],"ensures":[149],"up-to-date":[150],"data,":[151],"eliminates":[153],"potential":[155],"misuse":[157],"through":[158],"data":[159],"manipulation.":[160],"also":[162,186],"propose":[163],"useful":[165,202],"evaluation":[166,196],"methodology":[167],"that":[168,197],"addresses":[169],"hyperparameter":[170],"selection":[171],"enables":[173],"indirect":[174],"comparisons":[175],"with":[176],"alternative":[177],"approaches":[178],"datasets.":[182],"Finally,":[183],"work":[185],"contributes":[187],"large":[189],"scale":[190],"retrospective":[191],"matching":[193],"dataset":[194],"hope":[199],"will":[200],"be":[201],"further":[204],"research":[205],"this":[207],"field.":[208],"quite":[212],"effective;":[213],"approach,":[217],"expert":[218],"judges":[219],"rated":[220],"38%":[221],"as":[225,232,238,247],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Very":[228],"Relevant</i>":[229,242],";":[230,236,243],"33%":[231],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Relevant</i>":[235],"24%":[237],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Slightly":[241],"only":[245],"5%":[246],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Irrelevant</i>":[250],".":[251]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}