{"id":"https://openalex.org/W4412376943","doi":"https://doi.org/10.1145/3726302.3730131","title":"From Professional Search to Generative Deep Research Systems: How Can Expert Oversight Improve Search Outcomes?","display_name":"From Professional Search to Generative Deep Research Systems: How Can Expert Oversight Improve Search Outcomes?","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412376943","doi":"https://doi.org/10.1145/3726302.3730131"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3730131","doi":"https://doi.org/10.1145/3726302.3730131","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730131","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730131","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730131","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092362852","display_name":"Samy Ateia","orcid":"https://orcid.org/0009-0000-2622-9194","observed_orcids":["https://orcid.org/0009-0000-2622-9194"]},"institutions":[{"id":"https://openalex.org/I60668342","display_name":"University of Regensburg","ror":"https://ror.org/01eezs655","country_code":"DE","type":"education","lineage":["https://openalex.org/I60668342"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Samy Ateia","raw_affiliation_strings":["Department of Information Science, University of Regensburg, Regensburg, Germany"],"raw_orcid":"https://orcid.org/0009-0000-2622-9194","affiliations":[{"raw_affiliation_string":"Department of Information Science, University of Regensburg, Regensburg, Germany","institution_ids":["https://openalex.org/I60668342"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5092362852"],"corresponding_institution_ids":["https://openalex.org/I60668342"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14785,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4212","last_page":"4212"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9994999766349792,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9994999766349792,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.00019999999494757503,"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":0.0,"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/generative-search","display_name":"generative search","score":0.8820000290870667},{"id":"https://openalex.org/keywords/expert-feedback","display_name":"expert feedback","score":0.6129999756813049},{"id":"https://openalex.org/keywords/systematic-reviews","display_name":"systematic reviews","score":0.6990000009536743},{"id":"https://openalex.org/keywords/query-formulation","display_name":"query formulation","score":0.5960000157356262},{"id":"https://openalex.org/keywords/relevance-assessment","display_name":"relevance assessment","score":0.871999979019165},{"id":"https://openalex.org/keywords/information-extraction","display_name":"information extraction","score":0.953000009059906},{"id":"https://openalex.org/keywords/biomedical-question-answering","display_name":"biomedical question answering","score":0.6539999842643738},{"id":"https://openalex.org/keywords/interactive-information-retrieval","display_name":"interactive information retrieval","score":0.5989999771118164},{"id":"https://openalex.org/keywords/query-refinement","display_name":"query refinement","score":0.5400000214576721},{"id":"https://openalex.org/keywords/ai-reliability","display_name":"AI reliability","score":0.32100000977516174},{"id":"https://openalex.org/keywords/user-control","display_name":"user control","score":0.41600000858306885}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6816481351852417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6256474256515503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4601391851902008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4573724567890167},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4415859878063202}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3726302.3730131","doi":"https://doi.org/10.1145/3726302.3730131","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730131","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730131","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3726302.3730131","doi":"https://doi.org/10.1145/3726302.3730131","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730131","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730131","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412376943.pdf","grobid_xml":"https://content.openalex.org/works/W4412376943.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2909523012","https://openalex.org/W4409166206","https://openalex.org/W4409767160"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Generative":[0],"AI":[1],"(GenAI)":[2],"models":[3,307],"are":[4],"increasingly":[5],"employed":[6],"for":[7,141,191,313,322,378],"professional":[8,27,129,193,288,379],"search":[9,28,86,103,109,130,189,212,264,289],"tasks,":[10],"from":[11,36,134,228],"enterprise":[12],"copilots":[13],"to":[14,51,224,254,267,292,329,371],"systematic":[15,70,145,366],"reviews.":[16],"Recently":[17],"introduced":[18,318],"''deep":[19],"research''":[20],"products":[21],"(OpenAI,":[22],"Google),":[23],"marketed":[24],"as":[25,66,171,357,363,365],"automated":[26,269,311,345],"agents,":[29],"promise":[30,122],"comprehensive":[31],"query":[32,215],"generation":[33],"and":[34,54,69,76,101,144,176,184,219,235,276,317,340,360],"synthesis":[35],"large":[37],"document":[38],"sets.":[39],"However,":[40,128],"this":[41,198],"drive":[42],"toward":[43,231],"automation":[44,230],"risks":[45],"minimizing":[46],"user":[47,77,99],"involvement,":[48],"potentially":[49],"leading":[50],"misaligned":[52],"results":[53],"inappropriate":[55],"reliance":[56],"on":[57,178,297,352],"AI-generated":[58],"outputs.":[59],"Professional":[60],"search,":[61],"especially":[62],"in":[63,123,271,308],"domains":[64],"such":[65,170,356],"biomedical":[67,314,353],"research":[68,240],"reviews,":[71],"necessitates":[72],"expert":[73,204,233,245,285,294],"input,":[74],"transparency,":[75],"control,":[78],"requirements":[79],"often":[80],"not":[81],"met":[82],"by":[83],"current":[84,187],"generative":[85,108,188,211,263,380],"tools.":[87,160],"Interactive":[88],"Information":[89],"Retrieval":[90],"(IIR)":[91],"literature":[92],"has":[93],"long":[94],"emphasized":[95],"the":[96,182,226,281,303,373],"value":[97,374],"of":[98,107,113,186,209,273,283,305,375],"interactions":[100],"iterative":[102],"refinement.":[104],"The":[105],"rise":[106],"introduces":[110],"innovative":[111],"methods":[112],"accessing":[114],"information":[115,126,220],"through":[116],"natural":[117],"language":[118],"interactions,":[119],"which":[120],"show":[121],"addressing":[124],"complex":[125],"needs.":[127],"tasks":[131],"differ":[132],"substantially":[133],"general":[135],"consumer":[136],"searches,":[137],"involving":[138],"transparent":[139],"criteria":[140],"relevance":[142,217],"judgments":[143],"data":[146],"extraction":[147],"processes.":[148],"Despite":[149],"early":[150],"evidence":[151],"suggesting":[152],"increased":[153,232],"productivity":[154],"among":[155],"knowledge":[156],"workers":[157],"using":[158],"GenAI":[159,306],"these":[161,196],"systems":[162,190,253],"also":[163],"exhibit":[164],"substantial":[165],"shortcomings.":[166],"Studies":[167],"highlight":[168,372],"issues":[169],"unsupported":[172],"claims,":[173],"inaccurate":[174],"citations,":[175],"overreliance":[177],"generated":[179,324],"content,":[180],"questioning":[181],"reliability":[183],"suitability":[185],"high-stakes":[192],"use.":[194],"Given":[195],"challenges,":[197],"work":[199],"explores":[200],"systematically":[201,248],"integrating":[202],"structured":[203],"feedback":[205,246,286,335],"at":[206],"multiple":[207],"stages":[208],"a":[210,261,309,332],"process,":[213],"specifically":[214],"formulation,":[216],"judgments,":[218],"extraction.":[221],"We":[222],"aim":[223],"shift":[225],"focus":[227],"full":[229],"control":[234],"quality":[236],"assurance.":[237],"Our":[238],"key":[239],"questions":[241],"are:RQ1:":[242],"How":[243,259],"can":[244],"be":[247],"integrated":[249],"into":[250],"GenAI-driven":[251],"retrieval":[252,274,339],"improve":[255,287,338],"result":[256],"quality?":[257],"RQ2:":[258],"does":[260],"feedback-driven":[262],"system":[265,321],"compare":[266],"fully":[268,310,344],"approaches":[270],"terms":[272],"effectiveness":[275,342],"task":[277,341],"performance?":[278],"RQ3:":[279],"Does":[280],"integration":[282],"human":[284,376],"outcomes":[290],"compared":[291],"GenAI-simulated":[293],"feedback?":[295],"Building":[296],"our":[298,349],"earlier":[299],"experiments":[300],"that":[301],"assessed":[302],"performance":[304],"setting":[312],"question":[315],"answering":[316],"an":[319],"interactive":[320],"refining":[323],"queries,":[325],"we":[326,369],"now":[327],"seek":[328],"evaluate":[330],"how":[331],"structured,":[333],"human-in-the-loop":[334],"approach":[336],"might":[337],"over":[343],"pipelines.":[346],"By":[347],"evaluating":[348],"proposed":[350],"framework":[351],"Q&A":[354],"datasets":[355],"CLEF":[358],"BioASQ":[359],"TREC":[361],"BioGen":[362],"well":[364],"review":[367],"datasets,":[368],"want":[370],"guidance":[377],"search.":[381]},"counts_by_year":[],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2025-10-10T00:00:00"}
