{"id":"https://openalex.org/W7128812836","doi":"https://doi.org/10.3233/faia251721","title":"Automating Data Fusion: Techniques for Handling of Join Scenarios","display_name":"Automating Data Fusion: Techniques for Handling of Join Scenarios","publication_year":2026,"publication_date":"2026-02-12","ids":{"openalex":"https://openalex.org/W7128812836","doi":"https://doi.org/10.3233/faia251721"},"language":null,"primary_location":{"id":"doi:10.3233/faia251721","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251721","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia251721","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125978747","display_name":"Finn Dohrn","orcid":null},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]},{"id":"https://openalex.org/I70451448","display_name":"HAW Hamburg","ror":"https://ror.org/00fkqwx76","country_code":"DE","type":"education","lineage":["https://openalex.org/I70451448"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Finn Dohrn","raw_affiliation_strings":["Hamburg University of Applied Science"],"raw_orcid":"https://orcid.org/0009-0001-3926-1609","affiliations":[{"raw_affiliation_string":"Hamburg University of Applied Science","institution_ids":["https://openalex.org/I70451448","https://openalex.org/I159176309"]}]},{"author_position":"last","author":{"id":null,"display_name":"Marina Tropmann-Frick","orcid":"https://orcid.org/0000-0003-1623-5309"},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]},{"id":"https://openalex.org/I70451448","display_name":"HAW Hamburg","ror":"https://ror.org/00fkqwx76","country_code":"DE","type":"education","lineage":["https://openalex.org/I70451448"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marina Tropmann-Frick","raw_affiliation_strings":["Hamburg University of Applied Science"],"raw_orcid":"https://orcid.org/0000-0003-1623-5309","affiliations":[{"raw_affiliation_string":"Hamburg University of Applied Science","institution_ids":["https://openalex.org/I70451448","https://openalex.org/I159176309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2988715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.6017000079154968,"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":0.6017000079154968,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.20309999585151672,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.025100000202655792,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/join","display_name":"Join (topology)","score":0.8510000109672546},{"id":"https://openalex.org/keywords/joins","display_name":"Joins","score":0.8001000285148621},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5303000211715698},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5108000040054321},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.4401000142097473},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.412200003862381},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.38580000400543213},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.37950000166893005}],"concepts":[{"id":"https://openalex.org/C2776124973","wikidata":"https://www.wikidata.org/wiki/Q3183033","display_name":"Join (topology)","level":2,"score":0.8510000109672546},{"id":"https://openalex.org/C2778692605","wikidata":"https://www.wikidata.org/wiki/Q4041866","display_name":"Joins","level":2,"score":0.8001000285148621},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7465999722480774},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6010000109672546},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5303000211715698},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5108000040054321},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.4401000142097473},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.412200003862381},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2994000017642975},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28029999136924744},{"id":"https://openalex.org/C135572916","wikidata":"https://www.wikidata.org/wiki/Q193351","display_name":"Data warehouse","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C1306188","wikidata":"https://www.wikidata.org/wiki/Q4060687","display_name":"Nested loop join","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27239999175071716},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.2644999921321869}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia251721","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251721","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia251721","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251721","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"real-world":[1],"data":[2,156],"integration":[3,139],"scenarios,":[4],"traditional":[5],"equi-joins":[6],"and":[7,17,82,110],"other":[8],"join":[9,50,77,90,108,123],"techniques":[10],"have":[11],"huge":[12],"difficulties":[13],"due":[14],"to":[15,79,119,162],"heterogenity":[16],"inconsistencies":[18],"in":[19,105,166],"attribute":[20,95],"values.":[21],"To":[22],"address":[23],"this":[24],"challenge,":[25],"we":[26],"present":[27],"AutoStarJoin,":[28],"a":[29],"technique":[30],"for":[31,36,61,138],"automated":[32,47],"joins":[33],"specifically":[34],"designed":[35],"star-join":[37],"scenarios.":[38],"The":[39],"core":[40],"contribution":[41],"of":[42,49,101,107,132,153],"our":[43,135],"approach":[44,65,136],"is":[45,118,147,158],"the":[46,59,68,89,99,150],"detection":[48],"attributes":[51,78],"across":[52,113,121],"arbitrary":[53],"schemas,":[54],"reducing":[55],"or":[56],"even":[57],"eliminating":[58],"need":[60],"manual":[62],"specification.":[63],"Our":[64,116],"analyses":[66],"first":[67],"edit-based":[69],"distance":[70,86,103],"measures,":[71,87],"transforming":[72],"similar":[73],"string":[74],"values":[75],"within":[76],"facilitate":[80],"matching,":[81],"explores":[83],"then":[84],"token-based":[85],"refining":[88],"process":[91],"by":[92],"identifying":[93],"optimal":[94],"pairs.":[96],"We":[97,160],"evaluate":[98],"effectiveness":[100],"various":[102],"metrics":[104],"terms":[106],"quality":[109],"computational":[111],"efficiency":[112],"diverse":[114],"datasets.":[115],"goal":[117],"generalize":[120],"different":[122],"scenarios":[124],"without":[125],"requiring":[126],"domain-specific":[127],"parameter":[128],"tuning.":[129],"This":[130],"level":[131],"automation":[133],"makes":[134],"suitable":[137],"into":[140],"AutoML":[141],"pipelines":[142],"where":[143],"minimal":[144],"human":[145],"intervention":[146],"desired.":[148],"However,":[149],"correct":[151],"choice":[152],"parameters":[154],"per":[155],"set":[157],"crucial.":[159],"intend":[161],"implement":[163],"hyperparameter":[164],"optimization":[165],"further":[167],"research.":[168]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-14T00:00:00"}