{"id":"https://openalex.org/W2768459074","doi":"https://doi.org/10.1145/3159652.3159730","title":"Neural Ranking Models with Multiple Document Fields","display_name":"Neural Ranking Models with Multiple Document Fields","publication_year":2018,"publication_date":"2018-02-02","ids":{"openalex":"https://openalex.org/W2768459074","doi":"https://doi.org/10.1145/3159652.3159730","mag":"2768459074"},"language":"en","primary_location":{"id":"doi:10.1145/3159652.3159730","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3159652.3159730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101457713","display_name":"Hamed Zamani","orcid":"https://orcid.org/0000-0002-0800-3340"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hamed Zamani","raw_affiliation_strings":["University of Massachusetts Amherst &amp; Microsoft, Amherst, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst &amp; Microsoft, Amherst, MA, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048533217","display_name":"Bhaskar Mitra","orcid":"https://orcid.org/0000-0002-5270-5550"},"institutions":[{"id":"https://openalex.org/I4210108625","display_name":"Microsoft (United Kingdom)","ror":"https://ror.org/01rw27z95","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210108625"]},{"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":"Bhaskar Mitra","raw_affiliation_strings":["Microsoft &amp; University College London, Cambridge, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft &amp; University College London, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I4210108625","https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xia Song","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xia Song","raw_affiliation_strings":["Microsoft, Bellevue, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, Bellevue, WA, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055132321","display_name":"Nick Craswell","orcid":"https://orcid.org/0000-0002-9351-8137"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nick Craswell","raw_affiliation_strings":["Microsoft, Bellevue, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, Bellevue, WA, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210108985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030018356","display_name":"Saurabh Tiwary","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saurabh Tiwary","raw_affiliation_strings":["Microsoft, Bellevue, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, Bellevue, WA, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210108985"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":74,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"700","last_page":"708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9990000128746033,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9947999715805054,"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":0.7875612378120422},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7059784531593323},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6176324486732483},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5745055079460144},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5633441805839539},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5271130204200745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5224770307540894},{"id":"https://openalex.org/keywords/document-retrieval","display_name":"Document retrieval","score":0.4869309663772583},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.46827247738838196},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.446260929107666},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4343092441558838},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.4130042791366577},{"id":"https://openalex.org/keywords/document-structure-description","display_name":"Document Structure Description","score":0.41258540749549866},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34304505586624146},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3305252194404602},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08086651563644409}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7875612378120422},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7059784531593323},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6176324486732483},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5745055079460144},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5633441805839539},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5271130204200745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5224770307540894},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.4869309663772583},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.46827247738838196},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.446260929107666},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4343092441558838},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.4130042791366577},{"id":"https://openalex.org/C68699486","wikidata":"https://www.wikidata.org/wiki/Q265904","display_name":"Document Structure Description","level":3,"score":0.41258540749549866},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34304505586624146},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3305252194404602},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08086651563644409},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C8797682","wikidata":"https://www.wikidata.org/wiki/Q2115","display_name":"XML","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3159652.3159730","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3159652.3159730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W18398563","https://openalex.org/W1482214997","https://openalex.org/W1512789266","https://openalex.org/W1522301498","https://openalex.org/W1567631110","https://openalex.org/W1980809360","https://openalex.org/W2007815473","https://openalex.org/W2035820422","https://openalex.org/W2070811760","https://openalex.org/W2083745421","https://openalex.org/W2085030399","https://openalex.org/W2095705004","https://openalex.org/W2115584760","https://openalex.org/W2125771191","https://openalex.org/W2128877075","https://openalex.org/W2128892113","https://openalex.org/W2129235726","https://openalex.org/W2131876387","https://openalex.org/W2136189984","https://openalex.org/W2165613971","https://openalex.org/W2339829457","https://openalex.org/W2341132943","https://openalex.org/W2510769428","https://openalex.org/W2536015822","https://openalex.org/W2538374209","https://openalex.org/W2539671052","https://openalex.org/W2604436559","https://openalex.org/W2610935556","https://openalex.org/W2613589950","https://openalex.org/W2648699835","https://openalex.org/W2725049817","https://openalex.org/W2978329087","https://openalex.org/W3212575067"],"related_works":["https://openalex.org/W3082178636","https://openalex.org/W1521968289","https://openalex.org/W2782041652","https://openalex.org/W2027019938","https://openalex.org/W2079058854","https://openalex.org/W1518053583","https://openalex.org/W2948229652","https://openalex.org/W4288335753","https://openalex.org/W343133241","https://openalex.org/W3009633639"],"abstract_inverted_index":{"Deep":[0],"neural":[1,65,217],"networks":[2],"have":[3,15,40,52],"recently":[4],"shown":[5],"promise":[6],"in":[7,36,123,154],"the":[8,23,155,167,171,194,205,241,244],"ad-hoc":[9],"retrieval":[10],"task.":[11],"However,":[12],"such":[13,49,83,91],"models":[14,48,66],"often":[16],"been":[17,53],"based":[18],"on":[19,149],"one":[20,151],"field":[21,135,159],"of":[22,58,104,116,157,193,204,210,223,234,243],"document,":[24],"for":[25,106,166],"example":[26,107],"considering":[27],"document":[28,32,59,71,85,93,110,173,187,225],"title":[29,86],"only":[30],"or":[31,113],"body":[33],"only.":[34],"Since":[35,120],"practice":[37],"documents":[38],"typically":[39],"multiple":[41,70,228],"fields,":[42],"and":[43,87,125,181,196,230,246],"given":[44],"that":[45,77,185,219],"non-neural":[46,158],"ranking":[47],"as":[50,84,92,137,139],"BM25F":[51],"developed":[54],"to":[55,132,144,169,215,250],"take":[56,221],"advantage":[57,222],"structure,":[60,226],"this":[61],"paper":[62],"investigates":[63],"how":[64],"can":[67,78,96,220],"deal":[68],"with":[69,101,201,253],"fields.":[72],"We":[73,183],"introduce":[74,128],"a":[75,129,140,178,216,248],"model":[76],"consume":[79],"short":[80],"text":[81,89],"fields":[82,90,100,121,188],"long":[88],"body.":[94],"It":[95],"also":[97],"handle":[98,133],"multi-instance":[99],"variable":[102,235],"number":[103],"instances,":[105,136],"where":[108],"each":[109],"has":[111],"zero":[112],"more":[114],"instances":[115],"incoming":[117],"anchor":[118],"text.":[119,207],"vary":[122],"coverage":[124],"quality,":[126],"we":[127,161],"masking":[130],"method":[131,143],"missing":[134,231],"well":[138],"field-level":[141],"dropout":[142],"avoid":[145],"relying":[146],"too":[147],"much":[148],"any":[150],"field.":[152],"As":[153],"studies":[156],"weighting,":[160],"find":[162,184],"it":[163],"is":[164],"better":[165],"ranker":[168,218],"score":[170,180],"whole":[172],"jointly,":[174],"rather":[175],"than":[176],"generate":[177],"per-field":[179],"aggregate.":[182],"different":[186,191],"may":[189],"match":[190],"aspects":[192],"query":[195,206],"therefore":[197],"benefit":[198],"from":[199],"comparing":[200],"separate":[202],"representations":[203],"The":[208,237],"combination":[209],"techniques":[211,238],"introduced":[212],"here":[213],"leads":[214],"full":[224],"including":[227],"instance":[229,232],"data,":[233],"length.":[236],"significantly":[239],"enhance":[240],"performance":[242],"ranker,":[245],"outperform":[247],"learning":[249],"rank":[251],"baseline":[252],"hand-crafted":[254],"features.":[255]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":15}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
