{"id":"https://openalex.org/W2056699197","doi":"https://doi.org/10.1145/1458082.1458090","title":"Integrating web query results","display_name":"Integrating web query results","publication_year":2008,"publication_date":"2008-10-26","ids":{"openalex":"https://openalex.org/W2056699197","doi":"https://doi.org/10.1145/1458082.1458090","mag":"2056699197"},"language":"en","primary_location":{"id":"doi:10.1145/1458082.1458090","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1458082.1458090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM conference on Information and knowledge management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5022191055","display_name":"Shui\u2010Lung Chuang","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":"Shui-Lung Chuang","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA","University of Illinois at Urbana/Champaign, Urbana, IL, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"University of Illinois at Urbana/Champaign, Urbana, IL, USA#TAB#","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101880377","display_name":"Kevin Chen\u2013Chuan Chang","orcid":"https://orcid.org/0000-0003-0997-6803"},"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":"Kevin Chen-Chuan Chang","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA","University of Illinois at Urbana/Champaign, Urbana, IL, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"University of Illinois at Urbana/Champaign, Urbana, IL, USA#TAB#","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":0.7608,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.68253341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"33","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9998000264167786,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9976999759674072,"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/T11719","display_name":"Data Quality and Management","score":0.9966999888420105,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/schema-matching","display_name":"Schema matching","score":0.8435513973236084},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8233730792999268},{"id":"https://openalex.org/keywords/data-integration","display_name":"Data integration","score":0.6074070930480957},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6022601127624512},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.5833864808082581},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5549759864807129},{"id":"https://openalex.org/keywords/star-schema","display_name":"Star schema","score":0.5506229400634766},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5488621592521667},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4817254841327667},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.476764976978302},{"id":"https://openalex.org/keywords/database-schema","display_name":"Database schema","score":0.28672167658805847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16876620054244995},{"id":"https://openalex.org/keywords/database-design","display_name":"Database design","score":0.08254852890968323}],"concepts":[{"id":"https://openalex.org/C2777327318","wikidata":"https://www.wikidata.org/wiki/Q1408390","display_name":"Schema matching","level":3,"score":0.8435513973236084},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8233730792999268},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.6074070930480957},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6022601127624512},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.5833864808082581},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5549759864807129},{"id":"https://openalex.org/C190703929","wikidata":"https://www.wikidata.org/wiki/Q1331138","display_name":"Star schema","level":4,"score":0.5506229400634766},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5488621592521667},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4817254841327667},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.476764976978302},{"id":"https://openalex.org/C30775581","wikidata":"https://www.wikidata.org/wiki/Q632285","display_name":"Database schema","level":3,"score":0.28672167658805847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16876620054244995},{"id":"https://openalex.org/C148840519","wikidata":"https://www.wikidata.org/wiki/Q1049878","display_name":"Database design","level":2,"score":0.08254852890968323}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1458082.1458090","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1458082.1458090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM conference on Information and knowledge management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W113372867","https://openalex.org/W1494141893","https://openalex.org/W1496591573","https://openalex.org/W1534024124","https://openalex.org/W2008896880","https://openalex.org/W2042389627","https://openalex.org/W2098016092","https://openalex.org/W2104086170","https://openalex.org/W2108267498","https://openalex.org/W2108489852","https://openalex.org/W2117058208","https://openalex.org/W2122604280","https://openalex.org/W2125838338","https://openalex.org/W2138745488","https://openalex.org/W2139135093","https://openalex.org/W2142104809","https://openalex.org/W2143607396","https://openalex.org/W2150365753","https://openalex.org/W2150721933","https://openalex.org/W2156543375","https://openalex.org/W2157060173","https://openalex.org/W2406080254","https://openalex.org/W6629830009","https://openalex.org/W6680506379"],"related_works":["https://openalex.org/W2376319089","https://openalex.org/W2034415381","https://openalex.org/W2546483132","https://openalex.org/W2351507151","https://openalex.org/W1528218860","https://openalex.org/W2361495691","https://openalex.org/W2280752832","https://openalex.org/W2016611314","https://openalex.org/W2036644834","https://openalex.org/W2366796078"],"abstract_inverted_index":{"The":[0],"emergence":[1],"of":[2,75,99],"numerous":[3],"data":[4,17,22,38,63,77,173],"sources":[5,81],"online":[6],"has":[7],"presented":[8],"a":[9,52,83,93,129,154],"pressing":[10],"need":[11],"for":[12,132,144,213],"more":[13,39,155,186],"automatic":[14],"yet":[15],"accurate":[16,187],"integration":[18],"techniques.":[19],"For":[20],"the":[21,35,61,73,76,80,104,162,214],"returned":[23],"from":[24,65,102,121,205],"querying":[25],"such":[26,140],"sources,":[27],"most":[28],"works":[29,210],"focus":[30],"on":[31,139],"how":[32],"to":[33,42,48,59,184,207],"extract":[34],"embedded":[36],"structured":[37],"accurately.":[40],"However,":[41],"eventually":[43],"provide":[44],"an":[45],"integrated":[46],"access":[47],"these":[49],"query":[50],"results,":[51],"last":[53],"but":[54],"not":[55],"least":[56],"step":[57],"is":[58,71,108],"combine":[60],"extracted":[62],"coming":[64],"different":[66],"sources.":[67,147],"A":[68],"critical":[69],"task":[70],"finding":[72],"correspondence":[74],"fields":[78],"between":[79],"-":[82],"problem":[84],"well":[85,212],"known":[86],"as":[87,152],"schema":[88,106,118,137,158,182],"matching.":[89],"Query":[90],"results":[91],"are":[92],"small":[94],"and":[95,112,134,175,200,209],"biased":[96],"sample":[97],"set":[98],"instances":[100,174],"obtained":[101,105],"sources;":[103],"information":[107],"thus":[109],"very":[110],"implicit":[111],"incomplete,":[113],"which":[114],"often":[115],"prevents":[116],"existing":[117],"matching":[119,138,151,183,188],"approaches":[120,202],"performing":[122],"effectively.":[123],"In":[124],"this":[125,166],"paper,":[126],"we":[127,169],"develop":[128],"novel":[130],"framework":[131,195],"understanding":[133],"effectively":[135],"supporting":[136],"instance-based":[141],"data,":[142],"especially":[143],"integrating":[145],"multiple":[146],"We":[148],"view":[149],"discovering":[150],"constructing":[153],"complete":[156],"domain":[157],"that":[159,193],"best":[160],"describes":[161],"input":[163],"data.":[164],"With":[165],"conceptual":[167],"view,":[168],"can":[170],"leverage":[171],"various":[172],"observed":[176],"regularities":[177],"seamlessly":[178],"with":[179],"holistic,":[180],"multiple-source":[181],"achieve":[185],"results.":[189],"Our":[190],"experiments":[191],"show":[192],"our":[194],"consistently":[196],"outperforms":[197],"baseline":[198],"pairwise":[199],"clustering-based":[201],"(raising":[203],"F-measure":[204],"50-89%":[206],"89-94%)":[208],"uniformly":[211],"surveyed":[215],"domains.":[216]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
