{"id":"https://openalex.org/W4387846873","doi":"https://doi.org/10.1145/3583780.3615172","title":"Product Entity Matching via Tabular Data","display_name":"Product Entity Matching via Tabular Data","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4387846873","doi":"https://doi.org/10.1145/3583780.3615172"},"language":"en","primary_location":{"id":"doi:10.1145/3583780.3615172","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3615172","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","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/A5004171452","display_name":"Ali Naeim abadi","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ali Naeim abadi","raw_affiliation_strings":["University of Alberta, Edmonton, AB, Canada"],"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068544743","display_name":"Mir Tafseer Nayeem","orcid":"https://orcid.org/0000-0002-4715-6059"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mir Tafseer Nayeem","raw_affiliation_strings":["University of Alberta, Edmonton, AB, Canada"],"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071837282","display_name":"Davood Rafiei","orcid":"https://orcid.org/0000-0003-2403-0266"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Davood Rafiei","raw_affiliation_strings":["University of Alberta, Edmonton, AB, Canada"],"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004171452"],"corresponding_institution_ids":["https://openalex.org/I154425047"],"apc_list":null,"apc_paid":null,"fwci":0.7457,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75361456,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4215","last_page":"4219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":1.0,"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":1.0,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9556000232696533,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.930899977684021,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8515096306800842},{"id":"https://openalex.org/keywords/serialization","display_name":"Serialization","score":0.7498297691345215},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6071264743804932},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5980925559997559},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.564399778842926},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.49052876234054565},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48361316323280334},{"id":"https://openalex.org/keywords/entity-linking","display_name":"Entity linking","score":0.456013947725296},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4336926341056824},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.41019734740257263},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39888107776641846},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3921724855899811},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34222155809402466},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3394439220428467},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.10793474316596985},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1019580066204071}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8515096306800842},{"id":"https://openalex.org/C52723943","wikidata":"https://www.wikidata.org/wiki/Q1127410","display_name":"Serialization","level":2,"score":0.7498297691345215},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6071264743804932},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5980925559997559},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.564399778842926},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.49052876234054565},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48361316323280334},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.456013947725296},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4336926341056824},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.41019734740257263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39888107776641846},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3921724855899811},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34222155809402466},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3394439220428467},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.10793474316596985},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1019580066204071},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583780.3615172","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3615172","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1964786778","https://openalex.org/W1981590391","https://openalex.org/W2073471108","https://openalex.org/W2107966677","https://openalex.org/W2164456230","https://openalex.org/W2546672044","https://openalex.org/W2595551253","https://openalex.org/W2612177096","https://openalex.org/W2798649495","https://openalex.org/W2945883855","https://openalex.org/W2946504770","https://openalex.org/W2966720878","https://openalex.org/W2980708516","https://openalex.org/W2985009327","https://openalex.org/W3010144884","https://openalex.org/W3011807731","https://openalex.org/W3014705052","https://openalex.org/W3119752913","https://openalex.org/W3123375411","https://openalex.org/W3134665270","https://openalex.org/W3174836606","https://openalex.org/W4221163653","https://openalex.org/W4239019441","https://openalex.org/W4306317280","https://openalex.org/W4316116694","https://openalex.org/W4317951181","https://openalex.org/W4321448364"],"related_works":["https://openalex.org/W4231356583","https://openalex.org/W1593760324","https://openalex.org/W2376159383","https://openalex.org/W2351439380","https://openalex.org/W2899905671","https://openalex.org/W4390136247","https://openalex.org/W2468279273","https://openalex.org/W2365228680","https://openalex.org/W2131622620","https://openalex.org/W2362327801"],"abstract_inverted_index":{"Product":[0],"Entity":[1],"Matching":[2],"(PEM)--a":[3],"subfield":[4],"of":[5],"record":[6],"linkage":[7],"that":[8,13,70,99],"focuses":[9],"on":[10,37,46,128],"linking":[11],"records":[12],"refer":[14],"to":[15,110,120,141],"the":[16,44,56,60,75,88],"same":[17],"product--is":[18],"a":[19,33,85,106],"challenging":[20],"task":[21],"for":[22],"many":[23,38],"entity":[24],"matching":[25],"models.":[26],"For":[27],"example,":[28],"recent":[29],"transformer":[30],"models":[31],"report":[32],"near-perfect":[34],"performance":[35,42],"score":[36],"datasets":[39,78,132,136],"while":[40],"their":[41],"is":[43,62],"lowest":[45],"PEM":[47,54,77],"datasets.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52],"study":[53],"under":[55],"common":[57],"setting":[58],"where":[59],"information":[61],"spread":[63],"over":[64],"text":[65],"and":[66,79,115,133,151],"tables.":[67],"We":[68,92],"show":[69,137],"adding":[71],"tables":[72,81],"can":[73,82],"enrich":[74],"existing":[76],"those":[80],"act":[83],"as":[84],"bridge":[86],"between":[87],"entities":[89],"being":[90],"matched.":[91],"also":[93],"propose":[94],"TATEM,":[95],"an":[96,116],"effective":[97],"solution":[98],"leverages":[100],"Pre-trained":[101],"Language":[102,146],"Models":[103,147],"(PLMs)":[104],"with":[105],"novel":[107],"serialization":[108],"technique":[109],"encode":[111],"tabular":[112],"product":[113],"data":[114],"attribute":[117],"ranking":[118],"module":[119],"make":[121],"our":[122,134],"model":[123],"more":[124],"data-efficient.":[125],"Our":[126],"experiments":[127],"both":[129],"current":[130],"benchmark":[131],"proposed":[135],"significant":[138],"improvements":[139],"compared":[140],"state-of-the-art":[142],"methods,":[143],"including":[144],"Large":[145],"(LLMs)":[148],"in":[149],"zero-shot":[150],"few-shot":[152],"settings.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}