{"id":"https://openalex.org/W3127985239","doi":"https://doi.org/10.1109/tkde.2021.3056894","title":"Deep Bayesian Active Learning for Learning to Rank: A Case Study in Answer Selection","display_name":"Deep Bayesian Active Learning for Learning to Rank: A Case Study in Answer Selection","publication_year":2021,"publication_date":"2021-02-07","ids":{"openalex":"https://openalex.org/W3127985239","doi":"https://doi.org/10.1109/tkde.2021.3056894","mag":"3127985239"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3056894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3056894","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-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/A5043193778","display_name":"Qunbo Wang","orcid":"https://orcid.org/0000-0002-5607-7854"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qunbo Wang","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5607-7854","affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114911190","display_name":"Wenjun Wu","orcid":"https://orcid.org/0000-0003-2998-8828"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjun Wu","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075011283","display_name":"Yuxing Qi","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxing Qi","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003170356","display_name":"Yongchi Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongchi Zhao","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":2.0473,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.88563983,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"34","issue":"11","first_page":"5251","last_page":"5262"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9936000108718872,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.982699990272522,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.795849084854126},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7214207649230957},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.688421368598938},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6565561294555664},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5299611687660217},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5003178119659424},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.49496883153915405},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4555136561393738},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4549105763435364},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.431448757648468},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.37790361046791077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11244618892669678}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.795849084854126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7214207649230957},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.688421368598938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6565561294555664},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5299611687660217},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5003178119659424},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.49496883153915405},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4555136561393738},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4549105763435364},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.431448757648468},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.37790361046791077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11244618892669678},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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":1,"locations":[{"id":"doi:10.1109/tkde.2021.3056894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3056894","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6746171846","display_name":"\u5927\u89c4\u6a21\u5728\u7ebf\u534f\u540c\u5b66\u4e60\u7684\u673a\u7406\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61532004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8544124041","display_name":null,"funder_award_id":"SKLSDE-2017ZX-03","funder_id":"https://openalex.org/F4320326978","funder_display_name":"State Key Laboratory of Software Development Environment"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326978","display_name":"State Key Laboratory of Software Development Environment","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W392180792","https://openalex.org/W1528361845","https://openalex.org/W1553262910","https://openalex.org/W1567512734","https://openalex.org/W1872312298","https://openalex.org/W1966443646","https://openalex.org/W2004672916","https://openalex.org/W2031972533","https://openalex.org/W2078887230","https://openalex.org/W2093347820","https://openalex.org/W2104042806","https://openalex.org/W2111051539","https://openalex.org/W2115305054","https://openalex.org/W2124244761","https://openalex.org/W2140539195","https://openalex.org/W2149427297","https://openalex.org/W2151401338","https://openalex.org/W2170347328","https://openalex.org/W2170960775","https://openalex.org/W2252217313","https://openalex.org/W2342049278","https://openalex.org/W2468484304","https://openalex.org/W2471138382","https://openalex.org/W2625559849","https://openalex.org/W2737434030","https://openalex.org/W2738347542","https://openalex.org/W2740823339","https://openalex.org/W2774918944","https://openalex.org/W2785787385","https://openalex.org/W2798587560","https://openalex.org/W2798820905","https://openalex.org/W2903158431","https://openalex.org/W2911333381","https://openalex.org/W2949071206","https://openalex.org/W2951266961","https://openalex.org/W2956371155","https://openalex.org/W2963696295","https://openalex.org/W2963742748","https://openalex.org/W2964282813","https://openalex.org/W6628826841","https://openalex.org/W6639393196","https://openalex.org/W6677732584","https://openalex.org/W6735374517","https://openalex.org/W6741950772","https://openalex.org/W6742003945","https://openalex.org/W6747231328","https://openalex.org/W6756615331","https://openalex.org/W6758759751","https://openalex.org/W6764214684"],"related_works":["https://openalex.org/W2293317945","https://openalex.org/W4323349240","https://openalex.org/W1786507113","https://openalex.org/W4318960487","https://openalex.org/W2597787948","https://openalex.org/W2621001737","https://openalex.org/W2499321295","https://openalex.org/W4231380332","https://openalex.org/W3120117209","https://openalex.org/W2954428433"],"abstract_inverted_index":{"Given":[0],"a":[1,4,24,47,67,120,131,163,181],"question":[2],"and":[3,60,175,187],"set":[5],"of":[6,14,26,83,109,199,207],"candidate":[7],"answers,":[8],"answer":[9,158],"selection":[10,159],"is":[11,192],"the":[12,16,81,110,157,176,197,205,208],"task":[13],"identifying":[15],"best":[17],"answer,":[18],"which":[19],"can":[20,42],"be":[21,93],"viewed":[22],"as":[23],"kind":[25],"learning-to-rank":[27,124],"tasks.":[28,125],"Learning":[29],"to":[30,62,70,79,194],"rank":[31],"arises":[32],"in":[33],"many":[34],"information":[35],"retrieval":[36],"applications,":[37],"where":[38],"deep":[39,48,97,103,115,133,173],"learning":[40,49,65,90,105,117,135,174],"models":[41],"achieve":[43],"inspiring":[44],"results.":[45],"Training":[46],"model":[50,169],"often":[51],"requires":[52],"large":[53],"scale":[54],"annotated":[55],"data":[56,78,164,189],"that":[57],"are":[58],"expensive":[59],"time-consuming":[61],"obtain.":[63],"Active":[64],"presents":[66,119],"promising":[68],"approach":[69],"this":[71,127],"problem":[72],"by":[73],"selecting":[74],"more":[75],"informative":[76],"training":[77],"reduce":[80],"amount":[82],"labelling":[84],"efforts":[85,113],"required.":[86],"Because":[87],"traditional":[88],"active":[89,104,116,134,200],"methods":[91],"cannot":[92],"directly":[94],"used":[95],"for":[96,123,156],"learning,":[98],"researchers":[99],"have":[100],"proposed":[101,193,209],"multiple":[102],"methods.":[106],"However,":[107],"none":[108],"previous":[111],"research":[112],"on":[114,138,168],"algorithms":[118],"specific":[121],"framework":[122,136],"In":[126],"work,":[128],"we":[129],"introduce":[130],"novel":[132],"based":[137,167],"<bold":[139,143,147,151],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[140,144,148,152],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">D</b>":[141],"eep":[142],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">E</b>":[145],"xpected":[146],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">L</b>":[149],"oss":[150],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">O</b>":[153],"ptimization":[154],"(DELO)":[155],"task.":[160],"It":[161],"adopts":[162],"acquisition":[165,190],"function":[166],"uncertainty":[170],"with":[171],"Bayesian":[172],"expected":[177],"loss":[178],"optimization.":[179],"Moreover,":[180],"two-step":[182],"batch-mode":[183],"procedure,":[184],"combining":[185],"DELO":[186],"other":[188],"strategies":[191],"further":[195],"improve":[196],"performance":[198],"learning.":[201],"Experimental":[202],"results":[203],"verify":[204],"effectiveness":[206],"framework.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}