{"id":"https://openalex.org/W4408222782","doi":"https://doi.org/10.1109/cisp-bmei64163.2024.10906087","title":"Tabular Data Classification via an Improved Gated Transformer","display_name":"Tabular Data Classification via an Improved Gated Transformer","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4408222782","doi":"https://doi.org/10.1109/cisp-bmei64163.2024.10906087"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei64163.2024.10906087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei64163.2024.10906087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5101623835","display_name":"Lu Huang","orcid":"https://orcid.org/0000-0002-1588-8669"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Huang","raw_affiliation_strings":["School of Computer Science and Technology, Southwest University of Science and Technology,Mianyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Southwest University of Science and Technology,Mianyang,China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014092332","display_name":"Anjie Peng","orcid":"https://orcid.org/0000-0001-9287-7536"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anjie Peng","raw_affiliation_strings":["School of Computer Science and Technology, Southwest University of Science and Technology,Mianyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Southwest University of Science and Technology,Mianyang,China","institution_ids":["https://openalex.org/I1297991670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1297991670"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.6614999771118164,"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/T10320","display_name":"Neural Networks and Applications","score":0.6614999771118164,"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":0.6596267819404602},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4605743885040283},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.453917533159256},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3415876626968384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33735573291778564},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1334267258644104},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12212276458740234},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.09765148162841797}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6596267819404602},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4605743885040283},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.453917533159256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3415876626968384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33735573291778564},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1334267258644104},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12212276458740234},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.09765148162841797}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei64163.2024.10906087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei64163.2024.10906087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2090091537","https://openalex.org/W2134837462","https://openalex.org/W2148002238","https://openalex.org/W2611002985","https://openalex.org/W2777186991","https://openalex.org/W2798664493","https://openalex.org/W2964182926","https://openalex.org/W2969724595","https://openalex.org/W3005680577","https://openalex.org/W3032089910","https://openalex.org/W3174082502","https://openalex.org/W3206529130","https://openalex.org/W4226059372","https://openalex.org/W4281260498","https://openalex.org/W4297322395","https://openalex.org/W4309113015","https://openalex.org/W4366213854","https://openalex.org/W4400762160","https://openalex.org/W6631881933","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Tabular":[0],"data":[1,11,83,95,101,119,204],"classification":[2,72],"is":[3,47,84,120,179],"a":[4,155,182,212],"key":[5,174],"task":[6],"in":[7],"the":[8,53,58,63,71,81,92,99,103,113,116,128,139,147,151,162,167,170,177,195,198,202,208],"field":[9],"of":[10,65,105,150,169,197],"analysis,":[12],"such":[13],"as":[14,98],"finance,":[15],"healthcare,":[16],"and":[17],"business":[18],"intelligence.":[19],"Although":[20],"traditional":[21],"Transformer":[22,54,143,171],"models":[23],"perform":[24],"well":[25],"at":[26,69],"working":[27,35],"with":[28,36],"sequential":[29,100],"data,":[30,67],"they":[31],"face":[32],"challenges":[33],"when":[34],"structured":[37,75,93],"tabular":[38,66,76,82,94,118,192,203],"data.":[39,77,152],"In":[40,206],"this":[41,79],"paper,":[42],"an":[43,123],"improved":[44,141],"gating":[45,157],"mechanism":[46,158],"proposed":[48,140,199,209],"to":[49,56,61,126,145,159,173],"be":[50,96],"integrated":[51],"into":[52,122,181],"architecture":[55,144],"enhance":[57],"model's":[59],"ability":[60],"capture":[62,127,146],"features":[64],"aiming":[68],"improving":[70,166],"performance":[73],"for":[74,102,185,201],"To":[78],"end,":[80],"first":[85],"unstructured":[86,117],"by":[87,138],"some":[88],"preprocessing":[89,114],"operations,":[90],"making":[91],"same":[97],"convenience":[104],"using":[106],"powerful":[107],"natural":[108],"language":[109],"processing":[110],"tools.":[111],"After":[112],"step,":[115],"converted":[121],"embedding":[124,133],"vector":[125],"initial":[129],"feature.":[130],"Then,":[131],"these":[132],"vectors":[134],"are":[135],"further":[136],"encoded":[137],"gated":[142],"intrinsic":[148],"characteristic":[149],"We":[153],"propose":[154],"new":[156],"dynamically":[160],"adjust":[161],"information":[163],"flow,":[164],"which":[165],"sensitivity":[168],"model":[172],"features.":[175],"Finally,":[176],"feature":[178],"fed":[180],"linear":[183],"classifier":[184],"classification.":[186,205],"Extensive":[187],"experiments":[188],"on":[189],"two":[190],"public":[191],"datasets":[193],"verify":[194],"effectiveness":[196],"method":[200,210],"addition,":[207],"achieved":[211],"higher":[213],"F1-score":[214],"than":[215],"existing":[216],"methods.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}