{"id":"https://openalex.org/W2963420970","doi":"https://doi.org/10.1145/3322640.3326738","title":"Exploiting Search Logs to Aid in Training and Automating Infrastructure for Question Answering in Professional Domains","display_name":"Exploiting Search Logs to Aid in Training and Automating Infrastructure for Question Answering in Professional Domains","publication_year":2019,"publication_date":"2019-06-17","ids":{"openalex":"https://openalex.org/W2963420970","doi":"https://doi.org/10.1145/3322640.3326738","mag":"2963420970"},"language":"en","primary_location":{"id":"doi:10.1145/3322640.3326738","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3322640.3326738","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law","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/A5022664529","display_name":"Filippo Pompili","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115483","display_name":"Thomson Reuters (Canada)","ror":"https://ror.org/01r4zz038","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210115483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Filippo Pompili","raw_affiliation_strings":["Thomson Reuters, Centre for AI &amp; Cognitive Computing, Toronto, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Thomson Reuters, Centre for AI &amp; Cognitive Computing, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I4210115483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025701458","display_name":"Jack G. Conrad","orcid":"https://orcid.org/0000-0001-9114-9385"},"institutions":[{"id":"https://openalex.org/I68384125","display_name":"Thomson Reuters (United States)","ror":"https://ror.org/00m7gt169","country_code":"US","type":"company","lineage":["https://openalex.org/I68384125"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jack G. Conrad\u2020","raw_affiliation_strings":["Thomson Reuters, Research &amp; Development, Saint Paul, Minnesota, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Thomson Reuters, Research &amp; Development, Saint Paul, Minnesota, USA","institution_ids":["https://openalex.org/I68384125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038305305","display_name":"Carter Kolbeck","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115483","display_name":"Thomson Reuters (Canada)","ror":"https://ror.org/01r4zz038","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210115483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Carter Kolbeck","raw_affiliation_strings":["Thomson Reuters, Centre for AI &amp; Cognitive Computing, Toronto, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Thomson Reuters, Centre for AI &amp; Cognitive Computing, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I4210115483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1093,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.38078914,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"93","last_page":"102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9983999729156494,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9916999936103821,"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":0.7828420400619507},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5997635126113892},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5826837420463562},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5491573214530945},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5313625335693359},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.4492899775505066},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.4475499093532562},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.44655081629753113},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4395492970943451},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4355364441871643},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.37951627373695374},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3224809765815735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23666110634803772}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7828420400619507},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5997635126113892},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5826837420463562},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5491573214530945},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5313625335693359},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.4492899775505066},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.4475499093532562},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.44655081629753113},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4395492970943451},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4355364441871643},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.37951627373695374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3224809765815735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23666110634803772},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3322640.3326738","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3322640.3326738","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W135190683","https://openalex.org/W1978658266","https://openalex.org/W1979459060","https://openalex.org/W2034117506","https://openalex.org/W2078875869","https://openalex.org/W2094206148","https://openalex.org/W2099548400","https://openalex.org/W2104290444","https://openalex.org/W2119934165","https://openalex.org/W2125771191","https://openalex.org/W2129235726","https://openalex.org/W2133156844","https://openalex.org/W2145376937","https://openalex.org/W2152314154","https://openalex.org/W2164052363","https://openalex.org/W2752228602","https://openalex.org/W2963341956","https://openalex.org/W2997701990","https://openalex.org/W4231856373","https://openalex.org/W4361217255"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2384605597","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2358755282","https://openalex.org/W2352448290"],"abstract_inverted_index":{"Developing":[0],"an":[1,91,145],"AI":[2],"question":[3],"answering":[4],"system":[5,321],"for":[6,17,23,219,357],"the":[7,49,65,148,174,185,228,232,240,250,262,323,330,334,344],"legal":[8,32,54],"and":[9,33,39,55,172,192,293,328],"regulatory":[10,34,56],"domain":[11],"requires":[12],"significant":[13],"ground":[14],"truth":[15],"annotations":[16,29,73],"what":[18,294],"constitutes":[19],"a":[20,24,86,95,138,253,283,287,318],"good":[21],"answer":[22,92],"given":[25,288],"question.":[26],"Collecting":[27],"these":[28,99],"from":[30,48,80,158,190],"qualified":[31],"professionals":[35],"is":[36,60,276,338],"time":[37],"consuming":[38],"expensive.":[40],"By":[41],"making":[42],"use":[43],"of":[44,52,132,151,180,196,203,216,242,252,290,307,325,347,363,366],"user":[45,81,87],"activity":[46,82],"data":[47,156,198,218,245,248,260,269,275,303,315,336,349,352],"query":[50],"logs":[51,83],"existing":[53],"search":[57],"engines,":[58],"it":[59,163],"possible":[61],"to":[62,101,105,109,168,176,199,230,278,282,304,350],"speed":[63],"up":[64],"annotation":[66],"collection":[67],"process":[68,175],"as":[69,71,121,224,226],"well":[70,225],"supplement":[72],"with":[74,90],"imputed":[75],"labels.":[76],"We":[77,97,182,238,310,341],"used":[78],"signals":[79,100],"indicating":[84],"that":[85,130,234,312],"affirmatively":[88],"engaged":[89],"after":[93],"entering":[94],"query.":[96],"leveraged":[98],"infer":[102],"suitable":[103],"answers":[104],"questions":[106],"without":[107],"needing":[108],"rely":[110],"on":[111,249,286,360],"annotators.":[112],"In":[113],"previous":[114],"research":[115],"efforts,":[116],"such":[117,144,159,236],"identification":[118],"was":[119],"known":[120],"Implicit":[122],"Relevance":[123],"Feedback":[124],"(IRF).":[125],"Our":[126],"investigations":[127],"have":[128],"determined":[129],"90%":[131],"our":[133],"IRF":[134,160],"candidates":[135],"contain":[136],"either":[137],"complete":[139],"or":[140],"partial":[141],"answer.":[142],"Given":[143],"elevated":[146],"baseline,":[147],"next":[149,220],"phase":[150],"this":[152],"project":[153],"involved":[154],"harvesting":[155],"derived":[157],"(we've":[161],"termed":[162],"\"silver":[164],"data\"":[165],"in":[166,210,322,339],"contrast":[167],"expert-annotated":[169],"\"gold":[170],"data\")":[171],"extending":[173],"significantly":[177],"larger":[178],"sets":[179],"data.":[181,205,367],"examine":[183],"how":[184,257,272],"approach":[186],"affects":[187],"performance":[188,251,281,295,332,355],"ranging":[189],"zero,":[191],"very":[193],"low":[194],"amounts":[195,202,215,306],"gold":[197,204,247,268,274,308,326,335,351],"substantially":[200],"higher":[201],"Such":[206],"efforts":[207],"can":[208,297,316],"result":[209],"producing":[211],"appreciably":[212],"more":[213],"reliable":[214],"training":[217],"generation":[221],"QA":[222,254,320],"systems":[223],"establishing":[227],"means":[229],"automate":[231],"infrastructure":[233],"supports":[235],"systems.":[237],"investigate":[239],"impact":[241,261],"including":[243],"silver":[244,259,291,302,314,348],"alongside":[246],"system.":[255],"Specifically:":[256],"does":[258],"cold":[263],"start":[264],"challenge":[265],"(when":[266],"no":[267],"exists":[270],"initially),":[271],"much":[273],"needed":[277],"achieve":[279],"comparable":[280],"model":[284],"trained":[285,359],"amount":[289],"data,":[292,327],"gains":[296],"be":[298],"realized":[299],"by":[300,353],"introducing":[301],"graduated":[305],"data?":[309],"show":[311,343],"leveraging":[313],"establish":[317],"preliminary":[319],"absence":[324],"boost":[329],"system's":[331],"once":[333],"workstream":[337],"place.":[340],"further":[342],"relative":[345],"efficacy":[346],"conducting":[354],"comparisons":[356],"models":[358],"varying":[361],"ratios":[362],"each":[364],"type":[365]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
