{"id":"https://openalex.org/W7139037275","doi":"https://doi.org/10.1145/3802004","title":"Accelerating Approximate Analytical Join Queries over Unstructured Data with Statistical Guarantees","display_name":"Accelerating Approximate Analytical Join Queries over Unstructured Data with Statistical Guarantees","publication_year":2026,"publication_date":"2026-05-18","ids":{"openalex":"https://openalex.org/W7139037275","doi":"https://doi.org/10.1145/3802004"},"language":"en","primary_location":{"id":"doi:10.1145/3802004","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3802004","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"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 ACM on Management of Data","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2603.16153","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129776416","display_name":"Yuxuan Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxuan Zhu","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, USA"],"raw_orcid":"https://orcid.org/0009-0001-6738-8930","affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103188343","display_name":"Tengjun Jin","orcid":"https://orcid.org/0009-0005-0353-4184"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tengjun Jin","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, USA"],"raw_orcid":"https://orcid.org/0009-0005-0353-4184","affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065967981","display_name":"Chenghao Mo","orcid":"https://orcid.org/0009-0003-9860-6325"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenghao Mo","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, USA"],"raw_orcid":"https://orcid.org/0009-0003-9860-6325","affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130139620","display_name":"Daniel Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Kang","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, USA"],"raw_orcid":"https://orcid.org/0000-0001-9860-9938","affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24165654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":"3","first_page":"1","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.7360000014305115,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.7360000014305115,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.07289999723434448,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.021400000900030136,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/blocking","display_name":"Blocking (statistics)","score":0.7073000073432922},{"id":"https://openalex.org/keywords/tuple","display_name":"Tuple","score":0.6740999817848206},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5722000002861023},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5078999996185303},{"id":"https://openalex.org/keywords/join","display_name":"Join (topology)","score":0.42739999294281006},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4156000018119812}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7408000230789185},{"id":"https://openalex.org/C144745244","wikidata":"https://www.wikidata.org/wiki/Q4927286","display_name":"Blocking (statistics)","level":2,"score":0.7073000073432922},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.6740999817848206},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5722000002861023},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5078999996185303},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43689998984336853},{"id":"https://openalex.org/C2776124973","wikidata":"https://www.wikidata.org/wiki/Q3183033","display_name":"Join (topology)","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4099000096321106},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.287200003862381},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26829999685287476},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.259799987077713}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3802004","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3802004","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"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 ACM on Management of Data","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2603.16153","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2603.16153","pdf_url":"https://arxiv.org/pdf/2603.16153","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2603.16153","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2603.16153","pdf_url":"https://arxiv.org/pdf/2603.16153","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309327","display_name":"Google","ror":"https://ror.org/00njsd438"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7139037275.pdf","grobid_xml":"https://content.openalex.org/works/W7139037275.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Analytical":[0],"join":[1],"queries":[2],"over":[3],"unstructured":[4],"data":[5,10,107],"are":[6],"increasingly":[7],"prevalent":[8],"in":[9,21,109],"analytics.":[11],"Applying":[12],"machine":[13],"learning":[14],"(ML)":[15],"models":[16,39],"to":[17,51,59,64,67,99,132,146,206,209],"label":[18],"every":[19],"pair":[20],"the":[22,32,110,118,124,134,137,151,169],"cross":[23,111],"product":[24,112],"of":[25,34,37,121,126,139],"tables":[26],"can":[27],"achieve":[28],"state-of-the-art":[29,210],"accuracy,":[30],"but":[31],"cost":[33],"pairwise":[35],"execution":[36],"ML":[38,158],"is":[40],"prohibitive.":[41],"Existing":[42],"algorithms,":[43],"such":[44],"as":[45,74,76],"embedding-based":[46,95,144],"blocking":[47,96,145,172],"and":[48,89,97,173,200],"sampling,":[49],"aim":[50],"reduce":[52],"this":[53],"cost.":[54],"However,":[55],"they":[56],"either":[57],"fail":[58],"provide":[60],"statistical":[61,87],"guarantees":[62,88],"(leading":[63],"errors":[65,203],"up":[66,205],"79%":[68],"higher":[69],"than":[70],"expected)":[71],"or":[72,182],"become":[73],"inefficient":[75],"uniform":[77],"sampling.":[78,174,185],"We":[79],"propose":[80],"blocking-augmented":[81],"sampling":[82,98,131],"(BaS),":[83],"which":[84],"simultaneously":[85],"achieves":[86],"high":[90],"efficiency.":[91,148],"BaS":[92,105,129,142,179,195],"optimally":[93],"orchestrates":[94],"mitigate":[100],"their":[101],"respective":[102],"limitations.":[103],"Specifically,":[104],"allocates":[106,168],"tuples":[108],"into":[113],"two":[114],"regimes":[115],"based":[116],"on":[117],"failure":[119],"modes":[120],"embeddings.":[122],"In":[123,136],"regime":[125,138],"false":[127,140],"negatives,":[128],"uses":[130],"estimate":[133],"result.":[135],"positives,":[141],"applies":[143],"improve":[147],"To":[149],"minimize":[150],"estimation":[152,202],"error":[153],"given":[154],"a":[155,162],"budget":[156,170],"for":[157],"executions,":[159],"we":[160,176,192],"design":[161],"novel":[163],"two-stage":[164],"algorithm":[165],"that":[166,178,194],"adaptively":[167],"between":[171],"Theoretically,":[175],"prove":[177],"asymptotically":[180],"outperforms":[181],"matches":[183],"standalone":[184],"On":[186],"real-world":[187],"datasets":[188],"across":[189],"different":[190],"modalities,":[191],"show":[193],"provides":[196],"valid":[197],"confidence":[198],"intervals":[199],"reduces":[201],"by":[204],"19\u00d7":[207],"compared":[208],"baselines.":[211]},"counts_by_year":[],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2026-03-20T00:00:00"}