{"id":"https://openalex.org/W2426026510","doi":"https://doi.org/10.1109/icdew.2016.7495649","title":"Utilizing user feedback to improve data integration systems","display_name":"Utilizing user feedback to improve data integration systems","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2426026510","doi":"https://doi.org/10.1109/icdew.2016.7495649","mag":"2426026510"},"language":"en","primary_location":{"id":"doi:10.1109/icdew.2016.7495649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdew.2016.7495649","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 32nd International Conference on Data Engineering Workshops (ICDEW)","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/A5038522506","display_name":"Ahmed El-Roby","orcid":"https://orcid.org/0000-0003-0737-3400"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ahmed El-Roby","raw_affiliation_strings":["University of Waterloo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5038522506"],"corresponding_institution_ids":["https://openalex.org/I151746483"],"apc_list":null,"apc_paid":null,"fwci":0.3883,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58049397,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"206","last_page":"210"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9998999834060669,"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":0.9995999932289124,"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/T10679","display_name":"Service-Oriented Architecture and Web Services","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8735038042068481},{"id":"https://openalex.org/keywords/rdf","display_name":"RDF","score":0.5738969445228577},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.5662075877189636},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5659300088882446},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.49797987937927246},{"id":"https://openalex.org/keywords/data-integration","display_name":"Data integration","score":0.4469684958457947},{"id":"https://openalex.org/keywords/linked-data","display_name":"Linked data","score":0.4412864148616791},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.43687543272972107},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41160067915916443},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3149813413619995},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15317362546920776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8735038042068481},{"id":"https://openalex.org/C147497476","wikidata":"https://www.wikidata.org/wiki/Q54872","display_name":"RDF","level":3,"score":0.5738969445228577},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.5662075877189636},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5659300088882446},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.49797987937927246},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.4469684958457947},{"id":"https://openalex.org/C69075417","wikidata":"https://www.wikidata.org/wiki/Q515701","display_name":"Linked data","level":3,"score":0.4412864148616791},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.43687543272972107},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41160067915916443},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3149813413619995},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15317362546920776},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdew.2016.7495649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdew.2016.7495649","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 32nd International Conference on Data Engineering Workshops (ICDEW)","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":20,"referenced_works":["https://openalex.org/W140982117","https://openalex.org/W1480615301","https://openalex.org/W1484056211","https://openalex.org/W1515851193","https://openalex.org/W1971684273","https://openalex.org/W1996505782","https://openalex.org/W2008896880","https://openalex.org/W2041265293","https://openalex.org/W2055515830","https://openalex.org/W2059268928","https://openalex.org/W2079694211","https://openalex.org/W2098388305","https://openalex.org/W2122843979","https://openalex.org/W2158418361","https://openalex.org/W2171262729","https://openalex.org/W2406114359","https://openalex.org/W2429792542","https://openalex.org/W2950262379","https://openalex.org/W6605714439","https://openalex.org/W6713576725"],"related_works":["https://openalex.org/W2283287182","https://openalex.org/W82112649","https://openalex.org/W1485690712","https://openalex.org/W2058923328","https://openalex.org/W3128827045","https://openalex.org/W2776293731","https://openalex.org/W2610919777","https://openalex.org/W2965230088","https://openalex.org/W4293389049","https://openalex.org/W1534806717"],"abstract_inverted_index":{"In":[0,195],"recent":[1],"years,":[2],"and":[3,48,61,74,235],"due":[4],"to":[5,32,44,91,104,127,144,151,208,215,228,231,242,257],"the":[6,9,33,42,59,118,141,149,157,161,190,203,210,213,216,221,232,239,250,259,262],"advances":[7],"of":[8,11,17,97,120,160,181,189,212,261],"field":[10],"information":[12],"extraction,":[13],"a":[14,64,77,114,129,186],"vast":[15],"amount":[16],"web":[18,60,79],"data":[19,23,54,94,142,163,183,191,271],"has":[20],"surfaced.":[21],"This":[22,40,177],"typically":[24],"comes":[25],"from":[26,58,245,268],"heterogeneous":[27,93,246,269],"sources":[28,47,55,143,164,192],"that":[29,125,169],"may":[30],"belong":[31],"same":[34],"domain,":[35,252],"but":[36],"have":[37],"different":[38,173],"schemas.":[39],"hinders":[41],"potential":[43],"integrate":[45,92],"these":[46,133,182],"exploit":[49],"their":[50,106],"semantic":[51,78],"properties.":[52],"These":[53],"are":[56,70,84,100,170],"extracted":[57],"represented":[62,71,85],"using":[63],"relational":[65,162,222],"model,":[66,80,223],"in":[67,81,117,132,172,220,249],"which":[68,82,112],"they":[69,83,99],"by":[72,146,238],"schemas":[73],"tables,":[75],"or":[76,165],"as":[86],"RDF":[87,174,251,270],"knowledge":[88,175],"bases.":[89,176],"Approaches":[90],"sources,":[95],"regardless":[96],"how":[98],"represented,":[101],"usually":[102],"try":[103,126],"infer":[105],"semantics":[107],"automatically":[108],"based":[109],"on":[110,136],"syntax,":[111],"is":[113,193,205],"difficult":[115],"task":[116],"absence":[119],"human":[121,130],"guidance.":[122],"Even":[123],"approaches":[124,134],"involve":[128],"element":[131],"rely":[135],"resolving":[137],"uncertainties":[138],"before":[139],"exposing":[140],"users":[145],"explicitly":[147],"asking":[148],"user":[150,200,217,226,255],"give":[152],"her":[153],"feedback":[154,201,227,256],"directly":[155],"over":[156,166],"mediated":[158,233],"schema":[159,234],"similar":[167],"entities":[168,267],"linked":[171],"delays":[178],"making":[179],"use":[180],"sets":[184],"until":[185],"perfect":[187],"integration":[188],"achieved.":[194],"our":[196],"work,":[197],"we":[198,224,253],"utilize":[199,225,254],"while":[202],"system":[204],"being":[206],"used":[207,237],"improve":[209,258],"quality":[211,260],"answers":[214,244],"queries.":[218],"Specifically,":[219],"apply":[229],"changes":[230],"mappings":[236],"query":[240],"processor":[241],"find":[243],"tables.":[247],"Also,":[248],"owl:sameAs":[263],"links":[264],"between":[265],"equivalent":[266],"sets.":[272]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}