{"id":"https://openalex.org/W2167439683","doi":"https://doi.org/10.1109/icde.2004.1319999","title":"Selectivity estimation for string predicates: overcoming the underestimation problem","display_name":"Selectivity estimation for string predicates: overcoming the underestimation problem","publication_year":2004,"publication_date":"2004-09-28","ids":{"openalex":"https://openalex.org/W2167439683","doi":"https://doi.org/10.1109/icde.2004.1319999","mag":"2167439683"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2004.1319999","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2004.1319999","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 20th International Conference on Data Engineering","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/A5038037154","display_name":"Surajit Chaudhuri","orcid":"https://orcid.org/0000-0001-8252-5270"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Surajit Chaudhuri","raw_affiliation_strings":["Microsoft Research, Columbia University, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Columbia University, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Venkatesh Ganti","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Venkatesh Ganti","raw_affiliation_strings":["Microsoft Research, Columbia University, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Columbia University, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080063580","display_name":"Luis Gravano","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"L. Gravano","raw_affiliation_strings":["Microsoft Research, Columbia University, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Columbia University, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038037154"],"corresponding_institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":5.8568,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.95998471,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"227","last_page":"238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9979000091552734,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9973999857902527,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.7927768230438232},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7743186950683594},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7568275332450867},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6691581606864929},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.500328540802002},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4771285057067871},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4429045021533966},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.44157400727272034},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.42779120802879333},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.415187805891037},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20080029964447021},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12730374932289124},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10312733054161072}],"concepts":[{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.7927768230438232},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7743186950683594},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7568275332450867},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6691581606864929},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.500328540802002},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4771285057067871},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4429045021533966},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44157400727272034},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.42779120802879333},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.415187805891037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20080029964447021},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12730374932289124},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10312733054161072},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icde.2004.1319999","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2004.1319999","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 20th International Conference on Data Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.10.4515","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.4515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www1.cs.columbia.edu/~gravano/Papers/2004/icde04.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.124.9982","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.9982","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/users/vganti/papers/stringpreds_icde04.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W119813091","https://openalex.org/W182248535","https://openalex.org/W1594031697","https://openalex.org/W1943106404","https://openalex.org/W1984629602","https://openalex.org/W1987242992","https://openalex.org/W2005188603","https://openalex.org/W2040455459","https://openalex.org/W2075833184","https://openalex.org/W2112076978","https://openalex.org/W2132560950","https://openalex.org/W2147440220","https://openalex.org/W2212047990","https://openalex.org/W2330820318","https://openalex.org/W2912934387","https://openalex.org/W3085162807","https://openalex.org/W4212883601","https://openalex.org/W4246225718","https://openalex.org/W4252040602","https://openalex.org/W6607421326","https://openalex.org/W6640926852","https://openalex.org/W6669496669","https://openalex.org/W6676769703","https://openalex.org/W6679745300"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2347513417"],"abstract_inverted_index":{"Queries":[0],"with":[1],"(equality":[2],"or":[3],"LIKE)":[4],"selection":[5],"predicates":[6,24,39],"over":[7,63],"string":[8,23,38],"attributes":[9],"are":[10,25],"widely":[11],"used":[12],"in":[13,75],"relational":[14],"databases.":[15],"However,":[16],"state-of-the-art":[17],"techniques":[18],"for":[19,37],"estimating":[20],"selectivities":[21],"of":[22,56,70],"often":[26],"biased":[27],"towards":[28],"severely":[29],"underestimating":[30],"selectivities.":[31],"We":[32],"develop":[33],"accurate":[34],"selectivity":[35],"estimators":[36,72],"that":[40],"adapt":[41],"to":[42,73],"data":[43,65,77],"and":[44,47,51,78],"query":[45,79],"characteristics,":[46],"which":[48],"can":[49],"exploit":[50],"build":[52],"on":[53],"a":[54],"variety":[55],"existing":[57],"estimators.":[58],"A":[59],"thorough":[60],"experimental":[61],"evaluation":[62],"real":[64],"sets":[66],"demonstrates":[67],"the":[68],"resilience":[69],"our":[71],"variations":[74],"both":[76],"characteristics.":[80]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":5},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}
