{"id":"https://openalex.org/W2875652255","doi":"https://doi.org/10.1145/3221269.3223028","title":"Metadata-driven error detection","display_name":"Metadata-driven error detection","publication_year":2018,"publication_date":"2018-07-09","ids":{"openalex":"https://openalex.org/W2875652255","doi":"https://doi.org/10.1145/3221269.3223028","mag":"2875652255"},"language":"en","primary_location":{"id":"doi:10.1145/3221269.3223028","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3221269.3223028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Scientific and Statistical Database Management","raw_type":"proceedings-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/A5108549027","display_name":"Larysa Visengeriyeva","orcid":null},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Larysa Visengeriyeva","raw_affiliation_strings":["TU Berlin"],"affiliations":[{"raw_affiliation_string":"TU Berlin","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009128577","display_name":"Ziawasch Abedjan","orcid":"https://orcid.org/0000-0002-2846-1373"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ziawasch Abedjan","raw_affiliation_strings":["TU Berlin"],"affiliations":[{"raw_affiliation_string":"TU Berlin","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108549027"],"corresponding_institution_ids":["https://openalex.org/I4577782"],"apc_list":null,"apc_paid":null,"fwci":2.541,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.90007677,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9998000264167786,"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":0.9998000264167786,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9944999814033508,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9897000193595886,"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":0.8147599697113037},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.7438915967941284},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.7043333053588867},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.652028501033783},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5908963084220886},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5837994813919067},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5250741839408875},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.5167359709739685},{"id":"https://openalex.org/keywords/quality-assurance","display_name":"Quality assurance","score":0.5103654265403748},{"id":"https://openalex.org/keywords/false-positives-and-false-negatives","display_name":"False positives and false negatives","score":0.442523330450058},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.42451590299606323},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35131150484085083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29932236671447754}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8147599697113037},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.7438915967941284},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.7043333053588867},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.652028501033783},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5908963084220886},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5837994813919067},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5250741839408875},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.5167359709739685},{"id":"https://openalex.org/C106436119","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assurance","level":3,"score":0.5103654265403748},{"id":"https://openalex.org/C112789634","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False positives and false negatives","level":3,"score":0.442523330450058},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.42451590299606323},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35131150484085083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29932236671447754},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3221269.3223028","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3221269.3223028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Scientific and Statistical Database Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5400000214576721,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W605727707","https://openalex.org/W760598031","https://openalex.org/W1503398984","https://openalex.org/W1521736627","https://openalex.org/W1541280084","https://openalex.org/W1610496399","https://openalex.org/W1976732638","https://openalex.org/W2000836282","https://openalex.org/W2044469685","https://openalex.org/W2046298800","https://openalex.org/W2064766209","https://openalex.org/W2081186682","https://openalex.org/W2089206172","https://openalex.org/W2099637074","https://openalex.org/W2129018774","https://openalex.org/W2167333415","https://openalex.org/W2190899134","https://openalex.org/W2213275763","https://openalex.org/W2288244345","https://openalex.org/W2298871042","https://openalex.org/W2338990760","https://openalex.org/W2402007731","https://openalex.org/W2438792749","https://openalex.org/W2439326083","https://openalex.org/W2544486974","https://openalex.org/W2562283110","https://openalex.org/W2565701092","https://openalex.org/W2585438896","https://openalex.org/W2591700809","https://openalex.org/W2592807190","https://openalex.org/W2912934387","https://openalex.org/W2913066018","https://openalex.org/W4232478844"],"related_works":["https://openalex.org/W1557094818","https://openalex.org/W2183246718","https://openalex.org/W2499612753","https://openalex.org/W1973412793","https://openalex.org/W2099261052","https://openalex.org/W4292605373","https://openalex.org/W2951146195","https://openalex.org/W4226316650","https://openalex.org/W3123215897","https://openalex.org/W4214835788"],"abstract_inverted_index":{"Scientific":[0],"data":[1,13,20,40,67],"often":[2],"originates":[3],"from":[4,14,147],"multiple":[5,79,174],"sources":[6,16],"and":[7,109,143],"human":[8],"agents.":[9],"The":[10],"integration":[11],"of":[12,27,34,66,78,106,122,162],"different":[15,30],"must":[17],"also":[18,88],"resolve":[19],"quality":[21,31,41],"problems":[22,42],"that":[23,159],"might":[24,94],"occur":[25],"because":[26],"inconsistency":[28],"or":[29,73],"assurance":[32],"levels":[33],"the":[35,76,120,148],"sources.":[36],"To":[37],"identify":[38],"various":[39],"in":[43],"a":[44,98,103],"dataset,":[45],"it":[46,114],"is":[47,87,115],"necessary":[48],"to":[49,118],"use":[50],"several":[51],"error":[52,56,84,136],"detection":[53,57,85,137],"methods.":[54],"Existing":[55],"solutions":[58],"are":[59,141],"usually":[60],"tailored":[61],"towards":[62],"one":[63],"specific":[64],"type":[65],"errors,":[68],"such":[69],"as":[70,91],"rule":[71],"violations":[72],"outliers,":[74],"requiring":[75],"application":[77],"strategies.":[80],"Using":[81],"all":[82],"possible":[83],"methods":[86],"not":[89,116],"satisfying,":[90],"some":[92,111],"systems":[93],"perform":[95],"poorly":[96],"on":[97],"particular":[99],"dataset":[100,149],"by":[101],"producing":[102],"large":[104],"number":[105],"false":[107],"positives":[108],"missing":[110],"results.":[112],"However,":[113],"trivial":[117],"assess":[119],"effectiveness":[121],"each":[123],"strategy":[124],"upfront.":[125],"We":[126,152],"propose":[127],"two":[128],"new":[129],"holistic":[130],"approaches":[131,140],"for":[132],"effectively":[133],"combining":[134,163],"off-the-shelf":[135],"systems.":[138],"Our":[139],"learning-based":[142],"incorporate":[144],"metadata":[145],"extracted":[146],"at":[150],"hand.":[151],"empirically":[153],"show,":[154],"using":[155],"four":[156],"real-world":[157],"datasets,":[158],"our":[160],"method":[161],"error-detecting":[164],"strategies":[165],"achieves":[166],"an":[167],"average":[168],"F1":[169],"score":[170],"15%":[171],"higher":[172],"than":[173],"heuristics-based":[175],"baselines.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}