{"id":"https://openalex.org/W4399120442","doi":"https://doi.org/10.1145/3654823.3654875","title":"Explainable Customer Churn Prediction Model Based on Deep Learning","display_name":"Explainable Customer Churn Prediction Model Based on Deep Learning","publication_year":2024,"publication_date":"2024-03-22","ids":{"openalex":"https://openalex.org/W4399120442","doi":"https://doi.org/10.1145/3654823.3654875"},"language":"en","primary_location":{"id":"doi:10.1145/3654823.3654875","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","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/A5066259827","display_name":"Shiyang Li","orcid":"https://orcid.org/0000-0003-2023-0949"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4403386666","display_name":"Guangdong Technology College","ror":"https://ror.org/00f0z8g04","country_code":null,"type":"education","lineage":["https://openalex.org/I4403386666"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shiyang Li","raw_affiliation_strings":["School of Information Technology, Guangdong Technology College, China"],"raw_orcid":"https://orcid.org/0000-0003-2023-0949","affiliations":[{"raw_affiliation_string":"School of Information Technology, Guangdong Technology College, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4403386666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083889158","display_name":"Zelin Shen","orcid":"https://orcid.org/0009-0003-9623-7546"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I4403386666","display_name":"Guangdong Technology College","ror":"https://ror.org/00f0z8g04","country_code":null,"type":"education","lineage":["https://openalex.org/I4403386666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zelin Shen","raw_affiliation_strings":["School of Information Technology, Guangdong Technology College, China"],"raw_orcid":"https://orcid.org/0009-0003-9623-7546","affiliations":[{"raw_affiliation_string":"School of Information Technology, Guangdong Technology College, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4403386666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066259827"],"corresponding_institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I4403386666"],"apc_list":null,"apc_paid":null,"fwci":0.8378,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7853338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"282","last_page":"287"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10154","display_name":"Customer Service Quality and Loyalty","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11536","display_name":"Consumer Retail Behavior Studies","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8950060606002808},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7865068912506104},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.6614777445793152},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6421423554420471},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6272203326225281},{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.5732351541519165},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.541643500328064},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5256121158599854},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.506004273891449},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.4716833233833313},{"id":"https://openalex.org/keywords/customer-relationship-management","display_name":"Customer relationship management","score":0.41781190037727356},{"id":"https://openalex.org/keywords/sustenance","display_name":"Sustenance","score":0.4106397330760956},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1007651686668396}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8950060606002808},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7865068912506104},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.6614777445793152},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6421423554420471},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6272203326225281},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.5732351541519165},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.541643500328064},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5256121158599854},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.506004273891449},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.4716833233833313},{"id":"https://openalex.org/C98825075","wikidata":"https://www.wikidata.org/wiki/Q485643","display_name":"Customer relationship management","level":2,"score":0.41781190037727356},{"id":"https://openalex.org/C2776351498","wikidata":"https://www.wikidata.org/wiki/Q1434188","display_name":"Sustenance","level":2,"score":0.4106397330760956},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1007651686668396},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3654823.3654875","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2606176882","https://openalex.org/W2901502904","https://openalex.org/W2981180732","https://openalex.org/W2992861029","https://openalex.org/W3088138397","https://openalex.org/W3090045915","https://openalex.org/W3121980379","https://openalex.org/W3160940115","https://openalex.org/W3163580962","https://openalex.org/W3185676931","https://openalex.org/W3206832504","https://openalex.org/W3215022785","https://openalex.org/W4206497522","https://openalex.org/W4214561564","https://openalex.org/W4225407267","https://openalex.org/W4289812813","https://openalex.org/W4313557196"],"related_works":["https://openalex.org/W4308469503","https://openalex.org/W32988189","https://openalex.org/W2904737874","https://openalex.org/W80466363","https://openalex.org/W4389233021","https://openalex.org/W2399571531","https://openalex.org/W2947132063","https://openalex.org/W4288337828","https://openalex.org/W4390415670","https://openalex.org/W4287816717"],"abstract_inverted_index":{"Customer":[0],"churn":[1,36,45],"represents":[2],"a":[3],"significant":[4],"peril":[5],"to":[6,25,143],"the":[7,26,56,85,113,126,131,145,158],"sustenance":[8],"and":[9,17,60,71,169],"expansion":[10],"of":[11,29,118,137,166],"business":[12],"enterprises,":[13],"necessitating":[14],"proactive":[15],"anticipation":[16],"effective":[18],"management":[19],"strategies":[20],"by":[21],"organizations.":[22],"In":[23],"response":[24],"existing":[27],"issue":[28],"poor":[30],"interpretability":[31],"in":[32,106,130,164],"commonly":[33],"used":[34],"customer":[35,44,58,119],"prediction":[37,46,147],"models,":[38],"this":[39],"paper":[40],"proposes":[41],"an":[42],"interpretable":[43],"model":[47,53,87,92,114,160],"based":[48],"on":[49,151],"deep":[50],"learning.":[51],"The":[52,90,135],"first":[54],"preprocesses":[55],"raw":[57],"dataset":[59],"then":[61],"applies":[62],"three":[63,76],"different":[64],"sampling":[65],"techniques\u2014SMOTE":[66],"oversampling,":[67],"SMOTETomek":[68],"hybrid":[69],"sampling,":[70],"Tomek":[72],"Links":[73],"undersampling\u2014to":[74],"generate":[75],"new":[77],"datasets.":[78],"These":[79],"datasets":[80,155],"are":[81,101,141],"subsequently":[82],"fed":[83],"into":[84],"TabNet":[86,91],"for":[88,103,125],"training.":[89],"executes":[93],"multiple":[94],"decision":[95,133,139],"steps,":[96],"where":[97],"attention":[98,127],"transfer":[99,128],"modules":[100,129],"employed":[102],"feature":[104,110],"selection":[105],"each":[107],"step.":[108,134],"Following":[109],"transformation":[111],"modules,":[112],"learns":[115],"advanced":[116],"representations":[117],"features,":[120],"using":[121],"them":[122],"as":[123],"inputs":[124],"next":[132],"outputs":[136],"all":[138],"steps":[140],"aggregated":[142],"obtain":[144],"final":[146],"result.":[148],"Experimental":[149],"validation":[150],"two":[152],"publicly":[153],"available":[154],"demonstrates":[156],"that":[157],"proposed":[159],"outperforms":[161],"other":[162],"algorithms":[163],"terms":[165],"predictive":[167],"accuracy":[168],"F1":[170],"score,":[171],"while":[172],"maintaining":[173],"good":[174],"interpretability.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}