{"id":"https://openalex.org/W4396571411","doi":"https://doi.org/10.14778/3641204.3641211","title":"Data-Driven Insight Synthesis for Multi-Dimensional Data","display_name":"Data-Driven Insight Synthesis for Multi-Dimensional Data","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396571411","doi":"https://doi.org/10.14778/3641204.3641211"},"language":"en","primary_location":{"id":"doi:10.14778/3641204.3641211","is_oa":false,"landing_page_url":"http://dx.doi.org/10.14778/3641204.3641211","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102658449","display_name":"Junjie Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Junjie Xing","raw_affiliation_strings":["University of Michigan, Ann Arbor, Michigan, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352782","display_name":"Xinyu Wang","orcid":"https://orcid.org/0000-0002-1836-0202"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyu Wang","raw_affiliation_strings":["University of Michigan, Ann Arbor, Michigan, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033358246","display_name":"H. V. Jagadish","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. V. Jagadish","raw_affiliation_strings":["University of Michigan, Ann Arbor, Michigan, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102658449"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.2624,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.48212217,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"17","issue":"5","first_page":"1007","last_page":"1019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10799","display_name":"Data Visualization and Analytics","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.5109240412712097},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.370403528213501}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5109240412712097},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.370403528213501}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3641204.3641211","is_oa":false,"landing_page_url":"http://dx.doi.org/10.14778/3641204.3641211","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1762726187","https://openalex.org/W2038123353","https://openalex.org/W2102297485","https://openalex.org/W2138309709","https://openalex.org/W2151530263","https://openalex.org/W2257756289","https://openalex.org/W2275996142","https://openalex.org/W2483130659","https://openalex.org/W2496170334","https://openalex.org/W2513272121","https://openalex.org/W2626990892","https://openalex.org/W2735080104","https://openalex.org/W2762513422","https://openalex.org/W2768517636","https://openalex.org/W2775696413","https://openalex.org/W2795226127","https://openalex.org/W2912195676","https://openalex.org/W2963426888","https://openalex.org/W2969478830","https://openalex.org/W2996095251","https://openalex.org/W3014023550","https://openalex.org/W3035308065","https://openalex.org/W3046744391","https://openalex.org/W3082233550","https://openalex.org/W3082450350","https://openalex.org/W3092234597","https://openalex.org/W3105251181","https://openalex.org/W3169230937","https://openalex.org/W3197661828","https://openalex.org/W4247880210","https://openalex.org/W4248373945"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W4395014643","https://openalex.org/W4391913857","https://openalex.org/W2350741829"],"abstract_inverted_index":{"Exploratory":[0],"data":[1,6],"analysis":[2],"can":[3,133],"uncover":[4],"interesting":[5,115,140],"insights":[7,25],"from":[8,82],"data.":[9,84],"Current":[10],"methods":[11],"utilize":[12],"\"interestingness":[13,49,78],"measures\"":[14],"designed":[15],"based":[16,103],"on":[17,104],"system":[18],"designers'":[19],"perspectives,":[20],"thus":[21],"inherently":[22],"restricting":[23],"the":[24,95,105,145],"to":[26],"their":[27],"defined":[28],"scope.":[29],"These":[30],"systems,":[31],"consequently,":[32],"may":[33],"not":[34],"adequately":[35],"represent":[36],"a":[37,72,122,136],"broader":[38],"range":[39,138],"of":[40,114,139],"user":[41,65,128],"interests.":[42],"Furthermore,":[43],"most":[44],"existing":[45],"approaches":[46],"that":[47,80,92,131],"formulate":[48],"measure\"":[50,79],"are":[51,67],"rule-based,":[52],"which":[53],"makes":[54],"them":[55],"inevitably":[56],"brittle":[57],"and":[58,98,127],"often":[59],"requires":[60],"holistic":[61],"re-design":[62],"when":[63],"new":[64],"needs":[66],"discovered.":[68],"This":[69],"paper":[70],"presents":[71],"data-driven":[73],"technique":[74],"for":[75,111],"deriving":[76],"an":[77,88,99],"learns":[81],"annotated":[83],"We":[85,117],"further":[86],"develop":[87],"innovative":[89],"annotation":[90,96],"algorithm":[91,102],"significantly":[93],"reduces":[94],"cost,":[97],"insight":[100],"synthesis":[101],"Markov":[106],"Chain":[107],"Monte":[108],"Carlo":[109],"method":[110],"efficient":[112],"discovery":[113],"insights.":[116],"consolidate":[118],"these":[119],"ideas":[120],"into":[121],"system.":[123],"Our":[124],"experimental":[125],"outcomes":[126],"studies":[129],"demonstrate":[130],"DAISY":[132],"effectively":[134],"discover":[135],"broad":[137],"insights,":[141],"thereby":[142],"substantially":[143],"advancing":[144],"current":[146],"state-of-the-art.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
