{"id":"https://openalex.org/W4318147643","doi":"https://doi.org/10.1109/bigdata55660.2022.10020606","title":"Large Scale Windowed Matching","display_name":"Large Scale Windowed Matching","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4318147643","doi":"https://doi.org/10.1109/bigdata55660.2022.10020606"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020606","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020606","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big 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/A5073580921","display_name":"Mateusz Przyborowski","orcid":"https://orcid.org/0000-0002-7721-8433"},"institutions":[{"id":"https://openalex.org/I4654613","display_name":"University of Warsaw","ror":"https://ror.org/039bjqg32","country_code":"PL","type":"education","lineage":["https://openalex.org/I4654613"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Mateusz Przyborowski","raw_affiliation_strings":["University of Warsaw,Institute of Informatics,Warsaw,Poland","Institute of Informatics, University of Warsaw, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"University of Warsaw,Institute of Informatics,Warsaw,Poland","institution_ids":["https://openalex.org/I4654613"]},{"raw_affiliation_string":"Institute of Informatics, University of Warsaw, Warsaw, Poland","institution_ids":["https://openalex.org/I4654613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022921305","display_name":"Krzysztof Ciebiera","orcid":null},"institutions":[{"id":"https://openalex.org/I4654613","display_name":"University of Warsaw","ror":"https://ror.org/039bjqg32","country_code":"PL","type":"education","lineage":["https://openalex.org/I4654613"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Krzysztof Ciebiera","raw_affiliation_strings":["University of Warsaw,Institute of Informatics,Warsaw,Poland","Institute of Informatics, University of Warsaw, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"University of Warsaw,Institute of Informatics,Warsaw,Poland","institution_ids":["https://openalex.org/I4654613"]},{"raw_affiliation_string":"Institute of Informatics, University of Warsaw, Warsaw, Poland","institution_ids":["https://openalex.org/I4654613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071225072","display_name":"Krzysztof Stencel","orcid":"https://orcid.org/0000-0001-6356-4872"},"institutions":[{"id":"https://openalex.org/I4654613","display_name":"University of Warsaw","ror":"https://ror.org/039bjqg32","country_code":"PL","type":"education","lineage":["https://openalex.org/I4654613"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Krzysztof Stencel","raw_affiliation_strings":["University of Warsaw,Institute of Informatics,Warsaw,Poland","Institute of Informatics, University of Warsaw, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"University of Warsaw,Institute of Informatics,Warsaw,Poland","institution_ids":["https://openalex.org/I4654613"]},{"raw_affiliation_string":"Institute of Informatics, University of Warsaw, Warsaw, Poland","institution_ids":["https://openalex.org/I4654613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073580921"],"corresponding_institution_ids":["https://openalex.org/I4654613"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29726834,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"6253","last_page":"6255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9991000294685364,"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":0.9991000294685364,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9986000061035156,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.7851543426513672},{"id":"https://openalex.org/keywords/schema-matching","display_name":"Schema matching","score":0.6993029713630676},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.6876740455627441},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.660456657409668},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.6523737907409668},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.540611743927002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48471665382385254},{"id":"https://openalex.org/keywords/transaction-data","display_name":"Transaction data","score":0.41438430547714233},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36118167638778687},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15859180688858032},{"id":"https://openalex.org/keywords/data-integration","display_name":"Data integration","score":0.15443336963653564},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.10098704695701599},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06810960173606873},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06505775451660156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7851543426513672},{"id":"https://openalex.org/C2777327318","wikidata":"https://www.wikidata.org/wiki/Q1408390","display_name":"Schema matching","level":3,"score":0.6993029713630676},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.6876740455627441},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.660456657409668},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.6523737907409668},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.540611743927002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48471665382385254},{"id":"https://openalex.org/C127722929","wikidata":"https://www.wikidata.org/wiki/Q7833714","display_name":"Transaction data","level":3,"score":0.41438430547714233},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36118167638778687},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15859180688858032},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.15443336963653564},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.10098704695701599},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06810960173606873},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06505775451660156},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020606","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020606","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1555156738","https://openalex.org/W1614298861","https://openalex.org/W2008896880","https://openalex.org/W2150365753","https://openalex.org/W2295598076","https://openalex.org/W2795302121","https://openalex.org/W2965546485","https://openalex.org/W2990525732","https://openalex.org/W3116723379","https://openalex.org/W4285025484","https://openalex.org/W4293873702","https://openalex.org/W6633177592","https://openalex.org/W6636510571","https://openalex.org/W6749051156","https://openalex.org/W6839127861"],"related_works":["https://openalex.org/W2794103424","https://openalex.org/W1528218860","https://openalex.org/W3208717180","https://openalex.org/W2406112091","https://openalex.org/W2125859764","https://openalex.org/W2014400548","https://openalex.org/W4301779090","https://openalex.org/W2029826694","https://openalex.org/W4298139853","https://openalex.org/W2016247499"],"abstract_inverted_index":{"Missing":[0],"or":[1],"invalid":[2],"records":[3,28],"in":[4,35],"sales":[5],"data":[6,22],"are":[7],"a":[8,38,47,64],"common":[9],"obstacle":[10],"that":[11],"can":[12,32],"damage":[13],"the":[14,21,24,27,75],"overall":[15],"effectiveness":[16],"of":[17,26,37,66],"market":[18],"analysis.":[19],"Completing":[20],"on":[23,63],"basis":[25],"obtained":[29],"so":[30],"far":[31],"be":[33],"formulated":[34],"means":[36],"schema":[39,54],"matching":[40,55],"task.":[41],"In":[42],"this":[43],"paper":[44],"we":[45],"present":[46],"machine":[48],"learning":[49],"based":[50,62],"method":[51],"for":[52,56],"performing":[53],"transactional":[57],"data.":[58],"The":[59],"analysis":[60],"is":[61],"dataset":[65],"over":[67],"700.000":[68],"transactions":[69],"from":[70],"retail":[71],"stores.":[72],"We":[73],"confront":[74],"proposed":[76],"solution":[77],"with":[78],"manual":[79],"and":[80],"conventional":[81],"approaches.":[82]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
