{"id":"https://openalex.org/W4404181176","doi":"https://doi.org/10.14778/3685800.3685913","title":"Intelligent Agents for Data Exploration","display_name":"Intelligent Agents for Data Exploration","publication_year":2024,"publication_date":"2024-08-01","ids":{"openalex":"https://openalex.org/W4404181176","doi":"https://doi.org/10.14778/3685800.3685913"},"language":"en","primary_location":{"id":"doi:10.14778/3685800.3685913","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3685800.3685913","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-04728252v1/file/VLDB2024_Women_In_Database_Research_Award.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081664259","display_name":"Sihem Amer-Yahia","orcid":"https://orcid.org/0000-0002-6194-4502"},"institutions":[{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Sihem Amer-Yahia","raw_affiliation_strings":["CNRS, Univ. Grenoble Alpes"],"affiliations":[{"raw_affiliation_string":"CNRS, Univ. Grenoble Alpes","institution_ids":["https://openalex.org/I899635006","https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5081664259"],"corresponding_institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I899635006"],"apc_list":null,"apc_paid":null,"fwci":1.0808,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.82119726,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"17","issue":"12","first_page":"4521","last_page":"4530"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9984999895095825,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9984999895095825,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9969000220298767,"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":0.9896000027656555,"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":0.7237625122070312},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6185851097106934},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.5454531311988831},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.53350830078125},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.5192187428474426},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46758079528808594},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.4516611695289612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3910493552684784},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3503328263759613},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.34377145767211914}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7237625122070312},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6185851097106934},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.5454531311988831},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.53350830078125},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.5192187428474426},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46758079528808594},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.4516611695289612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3910493552684784},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3503328263759613},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34377145767211914},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.14778/3685800.3685913","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3685800.3685913","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-04728252v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04728252","pdf_url":"https://hal.science/hal-04728252v1/file/VLDB2024_Women_In_Database_Research_Award.pdf","source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal on Very Large Databases, 2024, 17 (12), pp.4521-4530. ⟨10.14778/3685800.3685913⟩","raw_type":"Journal articles"},{"id":"pmh:oai:HAL:hal-04728580v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04728580","pdf_url":"https://hal.science/hal-04728580v1/file/VLDB2024_Women_In_Database_Research_Award.pdf","source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the VLDB Endowment (PVLDB), 2024, ⟨10.14778/3685800.3685913⟩","raw_type":"Journal articles"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-04728252v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04728252","pdf_url":"https://hal.science/hal-04728252v1/file/VLDB2024_Women_In_Database_Research_Award.pdf","source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal on Very Large Databases, 2024, 17 (12), pp.4521-4530. ⟨10.14778/3685800.3685913⟩","raw_type":"Journal articles"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404181176.pdf","grobid_xml":"https://content.openalex.org/works/W4404181176.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W2015594732","https://openalex.org/W2053688343","https://openalex.org/W2145339207","https://openalex.org/W2963523627","https://openalex.org/W2984878977","https://openalex.org/W3031617143","https://openalex.org/W3037665057","https://openalex.org/W4288057685","https://openalex.org/W4289376325","https://openalex.org/W4306317685","https://openalex.org/W4311374336","https://openalex.org/W4379919478","https://openalex.org/W4385571232","https://openalex.org/W4385965642","https://openalex.org/W4386793443","https://openalex.org/W4387839203","https://openalex.org/W4389422760","https://openalex.org/W4391766565","https://openalex.org/W4392822461"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2045049461","https://openalex.org/W1978893398","https://openalex.org/W2201908702","https://openalex.org/W4381094582","https://openalex.org/W2369625323","https://openalex.org/W2364579609","https://openalex.org/W1977906818","https://openalex.org/W1522139108","https://openalex.org/W2353528968"],"abstract_inverted_index":{"Data":[0],"Exploration":[1],"is":[2,22,72],"an":[3,168],"incremental":[4],"process":[5],"that":[6,45,199],"helps":[7],"users":[8],"express":[9],"what":[10],"they":[11],"want":[12],"through":[13],"a":[14,81,105,108,116,120,125,129,133,186,201],"conversation":[15],"with":[16],"the":[17,25,76,142,160],"data.":[18],"Reinforcement":[19],"Learning":[20],"(RL)":[21],"one":[23],"of":[24,87,144,204],"most":[26],"notable":[27],"approaches":[28,198],"to":[29,74,80,151,158,195],"automate":[30],"data":[31,55,93,172,207],"exploration":[32,56,94],"and":[33,63,66,148,164,184,190],"several":[34],"solutions":[35,44],"have":[36],"been":[37,97],"proposed.":[38],"We":[39],"first":[40],"summarize":[41],"some":[42],"RL":[43,70,89,169],"were":[46],"built":[47],"for":[48,91,102,110,114,123,136,181],"different":[49],"applications.":[50],"In":[51],"this":[52],"context,":[53],"various":[54],"operators":[57],"are":[58],"leveraged":[59],"including":[60],"traditional":[61],"roll-up":[62],"drill-down":[64],"operations":[65],"text-based":[67],"operations.":[68],"An":[69],"agent":[71],"trained":[73],"generate":[75],"best":[77],"policy":[78,170],"according":[79],"hand-crafted":[82],"reward":[83],"function.":[84],"The":[85],"benefit":[86],"training":[88],"policies":[90],"specific":[92],"tasks":[95,183],"has":[96,155],"demonstrated":[98],"more":[99],"than":[100],"once":[101],"exploring":[103],"finding":[104],"needle":[106],"in":[107,132,171],"haystack,":[109],"serendipitous":[111],"galaxy":[112],"exploration,":[113],"helping":[115,124],"customer":[117],"land":[118],"on":[119],"satisfactory":[121],"product,":[122],"conference":[126],"chair":[127],"build":[128],"program":[130],"committee":[131],"stepwise":[134],"fashion,":[135],"summarizing":[137],"large":[138],"datasets,":[139],"etc.":[140],"With":[141],"advent":[143],"Large":[145],"Language":[146],"Models":[147],"their":[149],"ability":[150],"reason":[152],"sequentially,":[153],"it":[154],"become":[156],"legitimate":[157],"ask":[159],"question:":[161],"would":[162,176],"LLMs":[163,177],"AI":[165],"planning":[166],"outperform":[167],"exploration?":[173],"More":[174],"specifically,":[175],"help":[178],"circumvent":[179],"retraining":[180],"new":[182,202],"striking":[185],"balance":[187],"between":[188],"specificity":[189],"generality?":[191],"This":[192],"led":[193],"us":[194],"designing":[196],"LLM-powered":[197],"introduce":[200],"way":[203],"thinking":[205],"about":[206],"exploration.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2024-11-09T00:00:00"}