{"id":"https://openalex.org/W1998475090","doi":"https://doi.org/10.1145/1559845.1559869","title":"Exploiting context analysis for combining multiple entity resolution systems","display_name":"Exploiting context analysis for combining multiple entity resolution systems","publication_year":2009,"publication_date":"2009-06-29","ids":{"openalex":"https://openalex.org/W1998475090","doi":"https://doi.org/10.1145/1559845.1559869","mag":"1998475090"},"language":"en","primary_location":{"id":"doi:10.1145/1559845.1559869","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1559845.1559869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2009 ACM SIGMOD International Conference on Management of data","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/A5103028670","display_name":"Zhaoqi Chen","orcid":"https://orcid.org/0000-0001-9819-6643"},"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"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhaoqi Chen","raw_affiliation_strings":["Microsoft Corporation, Redmond, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078774287","display_name":"Dmitri V. Kalashnikov","orcid":"https://orcid.org/0009-0002-4180-1384"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dmitri V. Kalashnikov","raw_affiliation_strings":["University of California, Irvine, Irvine, CA, USA","University of California Irvine, IRVINE, CA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"University of California, Irvine, Irvine, CA, USA","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"University of California Irvine, IRVINE, CA, USA#TAB#","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010114060","display_name":"Sharad Mehrotra","orcid":"https://orcid.org/0000-0003-1667-5435"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sharad Mehrotra","raw_affiliation_strings":["University of California, Irvine, Irvine, CA, USA","University of California Irvine, IRVINE, CA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"University of California, Irvine, Irvine, CA, USA","institution_ids":["https://openalex.org/I204250578"]},{"raw_affiliation_string":"University of California Irvine, IRVINE, CA, USA#TAB#","institution_ids":["https://openalex.org/I204250578"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103028670"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":8.3317,"has_fulltext":false,"cited_by_count":82,"citation_normalized_percentile":{"value":0.97602312,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"207","last_page":"218"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9968000054359436,"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/T11106","display_name":"Data Management and Algorithms","score":0.9937999844551086,"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/computer-science","display_name":"Computer science","score":0.8179596066474915},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7170907855033875},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.612824559211731},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5543983578681946},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.551217257976532},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5305348634719849},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5269806385040283},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5067012906074524},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.46688714623451233},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4351414442062378},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4257199466228485},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.089129239320755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8179596066474915},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7170907855033875},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.612824559211731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5543983578681946},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.551217257976532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5305348634719849},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5269806385040283},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5067012906074524},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.46688714623451233},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4351414442062378},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4257199466228485},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.089129239320755},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1559845.1559869","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1559845.1559869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2009 ACM SIGMOD International Conference on Management of data","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.188.10","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.10","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ics.uci.edu/%7Edvk/pub/SIGMOD09_dvk.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.508.578","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.508.578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://dc-pubs.dbs.uni-leipzig.de/files/Exploiting context analysis for combining multiple entity resolution systems.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6200000047683716,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W4508078","https://openalex.org/W28412257","https://openalex.org/W51908901","https://openalex.org/W130948412","https://openalex.org/W1518900854","https://openalex.org/W1547897486","https://openalex.org/W1570448133","https://openalex.org/W1576226931","https://openalex.org/W1979629649","https://openalex.org/W1982678692","https://openalex.org/W1991254414","https://openalex.org/W2012604221","https://openalex.org/W2018063852","https://openalex.org/W2024770506","https://openalex.org/W2033073041","https://openalex.org/W2036216970","https://openalex.org/W2036987424","https://openalex.org/W2040925009","https://openalex.org/W2043141497","https://openalex.org/W2046020929","https://openalex.org/W2055405704","https://openalex.org/W2067566391","https://openalex.org/W2087183379","https://openalex.org/W2092708731","https://openalex.org/W2097645701","https://openalex.org/W2104302895","https://openalex.org/W2106602702","https://openalex.org/W2111625757","https://openalex.org/W2113586662","https://openalex.org/W2125035899","https://openalex.org/W2127425968","https://openalex.org/W2133236963","https://openalex.org/W2139280638","https://openalex.org/W2154785834","https://openalex.org/W2158275940","https://openalex.org/W2161682962","https://openalex.org/W2164456230","https://openalex.org/W2171179180","https://openalex.org/W2171472464","https://openalex.org/W2295351501","https://openalex.org/W2295665070","https://openalex.org/W2338376566","https://openalex.org/W2966207845","https://openalex.org/W4285719527","https://openalex.org/W6602040338","https://openalex.org/W6634531628"],"related_works":["https://openalex.org/W4376643315","https://openalex.org/W4324137541","https://openalex.org/W2900445707","https://openalex.org/W4285741730","https://openalex.org/W1191482210","https://openalex.org/W4285046548","https://openalex.org/W4210302090","https://openalex.org/W2806625726","https://openalex.org/W3092276832","https://openalex.org/W4375951447"],"abstract_inverted_index":{"Entity":[0],"Resolution":[1],"(ER)":[2],"is":[3,68],"an":[4],"important":[5],"real":[6],"world":[7],"problem":[8],"that":[9,100,181],"has":[10,47],"attracted":[11],"significant":[12],"research":[13],"interest":[14],"over":[15],"the":[16,52,71,83,87,98,108,148,152,158,170,182,192,196],"past":[17],"few":[18],"years.":[19],"It":[20],"deals":[21],"with":[22,82,157],"determining":[23],"which":[24,135],"object":[25],"descriptions":[26],"co-refer":[27],"in":[28,94,115,125],"a":[29,58,79,145,162],"dataset.":[30],"Due":[31],"to":[32,50,69,175,191],"its":[33],"practical":[34],"significance":[35],"for":[36],"data":[37,40],"mining":[38],"and":[39],"analysis":[41],"tasks":[42],"many":[43],"different":[44,120,126,176],"ER":[45,53,60,66,76,104,113,121,154],"approaches":[46,143],"been":[48],"developed":[49],"address":[51],"challenge.":[54],"This":[55],"paper":[56,96,167],"proposes":[57],"new":[59],"Ensemble":[61,67],"framework.":[62],"The":[63,91,128,141,166,178],"task":[64],"of":[65,73,85,89,117,147,151,195],"combine":[70],"results":[72],"multiple":[74],"base-level":[75,153],"systems":[77],"into":[78,161],"single":[80,103],"solution":[81],"goal":[84],"increasing":[86],"quality":[88,189],"ER.":[90],"framework":[92,129,171,184],"proposed":[93,183],"this":[95],"leverages":[97],"observation":[99],"often":[101],"no":[102],"method":[105],"always":[106],"performs":[107],"best,":[109],"consistently":[110],"outperforming":[111],"other":[112],"techniques":[114],"terms":[116],"quality.":[118],"Instead,":[119],"solutions":[122],"perform":[123],"better":[124],"contexts.":[127],"employs":[130],"two":[131,142],"novel":[132],"combining":[133],"approaches,":[134],"are":[136],"based":[137],"on":[138],"supervised":[139],"learning.":[140],"learn":[144],"mapping":[146],"clustering":[149,164],"decisions":[150],"systems,":[155],"together":[156],"local":[159],"context,":[160],"combined":[163],"decision.":[165],"empirically":[168],"studies":[169],"by":[172],"applying":[173],"it":[174],"domains.":[177],"experiments":[179],"demonstrate":[180],"achieves":[185],"significantly":[186],"higher":[187],"disambiguation":[188],"compared":[190],"current":[193],"state":[194],"art":[197],"solutions.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":6}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
