{"id":"https://openalex.org/W2787050809","doi":"https://doi.org/10.1109/icenco.2017.8289798","title":"Customer churn prediction model using data mining techniques","display_name":"Customer churn prediction model using data mining techniques","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2787050809","doi":"https://doi.org/10.1109/icenco.2017.8289798","mag":"2787050809"},"language":"en","primary_location":{"id":"doi:10.1109/icenco.2017.8289798","doi":"https://doi.org/10.1109/icenco.2017.8289798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icenco.2017.8289798","pdf_url":null,"source":{"id":"https://openalex.org/S4306418976","display_name":"International Computer Engineering Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2017 13th International Computer Engineering Conference (ICENCO)","raw_type":"proceedings-article"},"volume":null,"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/A5047114470","display_name":"Ibrahim M. M. Mitkees","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I890898191","display_name":"Modern Academy","ror":"https://ror.org/02exeb428","country_code":"EG","type":"education","lineage":["https://openalex.org/I890898191"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ibrahim M. M. Mitkees","raw_affiliation_strings":["Department of managment information system, Modern Academy, Cairo, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of managment information system, Modern Academy, Cairo, Egypt","institution_ids":["https://openalex.org/I890898191"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112060266","display_name":"Sherif M. Badr","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I890898191","display_name":"Modern Academy","ror":"https://ror.org/02exeb428","country_code":"EG","type":"education","lineage":["https://openalex.org/I890898191"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Sherif M Badr","raw_affiliation_strings":["Department of computer science, Modern Academy, Cairo, egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of computer science, Modern Academy, Cairo, egypt","institution_ids":["https://openalex.org/I890898191"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031009020","display_name":"Ahmed I. B. ElSeddawy","orcid":"https://orcid.org/0000-0001-5477-3509","observed_orcids":["https://orcid.org/0000-0001-5477-3509"]},"institutions":[{"id":"https://openalex.org/I59272784","display_name":"Arab Academy for Science, Technology, and Maritime Transport","ror":"https://ror.org/0004vyj87","country_code":"EG","type":"education","lineage":["https://openalex.org/I59272784"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ahmed Ibrahim Bahgat ElSeddawy","raw_affiliation_strings":["Department of Information Systems, Arab Academy for Science Technology & Maritime Transport (AASTMT), Cairo, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Arab Academy for Science Technology & Maritime Transport (AASTMT), Cairo, Egypt","institution_ids":["https://openalex.org/I59272784"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.3536,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.9306678,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"262","last_page":"268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":1.0,"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":1.0,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.0,"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"}},{"id":"https://openalex.org/T10154","display_name":"Customer Service Quality and Loyalty","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/customer-churn-prediction","display_name":"customer churn prediction","score":0.9900000095367432},{"id":"https://openalex.org/keywords/customer-retention","display_name":"customer retention","score":0.7229999899864197},{"id":"https://openalex.org/keywords/telecommunications-customers","display_name":"telecommunications customers","score":0.843999981880188},{"id":"https://openalex.org/keywords/consumer-behavior","display_name":"consumer behavior","score":0.6660000085830688},{"id":"https://openalex.org/keywords/consumer-characteristics","display_name":"consumer characteristics","score":0.8960000276565552},{"id":"https://openalex.org/keywords/clustering","display_name":"clustering","score":0.9129999876022339},{"id":"https://openalex.org/keywords/classification","display_name":"classification","score":0.9909999966621399},{"id":"https://openalex.org/keywords/association-rule-mining","display_name":"association rule mining","score":0.9309999942779541}],"concepts":[{"id":"https://openalex.org/C101276457","wikidata":"https://www.wikidata.org/wiki/Q5196474","display_name":"Customer retention","level":4,"score":0.7018442153930664},{"id":"https://openalex.org/C57660159","wikidata":"https://www.wikidata.org/wiki/Q5196460","display_name":"Customer intelligence","level":5,"score":0.6904221177101135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5725740790367126},{"id":"https://openalex.org/C130721881","wikidata":"https://www.wikidata.org/wiki/Q1146253","display_name":"Customer lifetime value","level":5,"score":0.564928412437439},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5490310192108154},{"id":"https://openalex.org/C43595421","wikidata":"https://www.wikidata.org/wiki/Q7939596","display_name":"Voice of the customer","level":5,"score":0.5304417014122009},{"id":"https://openalex.org/C98825075","wikidata":"https://www.wikidata.org/wiki/Q485643","display_name":"Customer relationship management","level":2,"score":0.5160557627677917},{"id":"https://openalex.org/C63207073","wikidata":"https://www.wikidata.org/wiki/Q1076010","display_name":"Customer to customer","level":5,"score":0.5132362842559814},{"id":"https://openalex.org/C2777500614","wikidata":"https://www.wikidata.org/wiki/Q738621","display_name":"Landline","level":3,"score":0.4887978732585907},{"id":"https://openalex.org/C31367271","wikidata":"https://www.wikidata.org/wiki/Q5196444","display_name":"Customer advocacy","level":4,"score":0.47180619835853577},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4344453811645508},{"id":"https://openalex.org/C53100981","wikidata":"https://www.wikidata.org/wiki/Q5196454","display_name":"Customer equity","level":5,"score":0.4198358654975891},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34146735072135925},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.34113460779190063},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3389620780944824},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.2701384425163269},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19754284620285034},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1461504101753235},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.11858740448951721},{"id":"https://openalex.org/C140781008","wikidata":"https://www.wikidata.org/wiki/Q1221081","display_name":"Service quality","level":3,"score":0.09975984692573547},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C2778707766","wikidata":"https://www.wikidata.org/wiki/Q202064","display_name":"Phone","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icenco.2017.8289798","doi":"https://doi.org/10.1109/icenco.2017.8289798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icenco.2017.8289798","pdf_url":null,"source":{"id":"https://openalex.org/S4306418976","display_name":"International Computer Engineering Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2017 13th International Computer Engineering Conference (ICENCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2115555003","https://openalex.org/W2140190241","https://openalex.org/W2142447009","https://openalex.org/W2185157108","https://openalex.org/W2336180536","https://openalex.org/W3103404646"],"related_works":["https://openalex.org/W2136737877","https://openalex.org/W4405126945","https://openalex.org/W2181491478","https://openalex.org/W2374335085","https://openalex.org/W4387607666","https://openalex.org/W2367060539","https://openalex.org/W2185206777","https://openalex.org/W7055795253","https://openalex.org/W4220882755","https://openalex.org/W3010430441"],"abstract_inverted_index":{"A":[0],"big":[1],"problem":[2],"that":[3,38,107,110],"encounters":[4],"businesses,":[5],"especially":[6],"telecommunications":[7],"business":[8,23],"is":[9,72,87,94],"`customer":[10],"churn'":[11],"this":[12,32],"occurs":[13],"when":[14],"a":[15,20,36,91],"customer":[16,42,92],"decides":[17],"to":[18,34,75,96],"leave":[19,97],"company's":[21],"landline":[22],"for":[24],"another":[25],"cable":[26],"competitor.":[27],"Therefore,":[28],"our":[29],"aim":[30],"beyond":[31],"study":[33],"build":[35],"model":[37],"will":[39,52],"predict":[40],"churn":[41],"through":[43],"defining":[44],"the":[45,69,76,85],"customer's":[46],"precise":[47],"behaviors":[48],"and":[49,61,66],"attributes.":[50],"We":[51],"use":[53],"data":[54],"mining":[55],"techniques":[56],"such":[57],"as":[58],"clustering,":[59],"classification":[60],"association":[62],"rule.":[63],"The":[64],"accuracy":[65],"preciseness":[67],"of":[68,78,90],"technique":[70],"used":[71],"so":[73],"essential":[74],"success":[77],"any":[79],"retention":[80],"attempting.":[81],"After":[82],"all,":[83],"if":[84],"company":[86,108],"not":[88],"aware":[89],"who":[93],"about":[95],"their":[98],"business;":[99],"no":[100],"proper":[101],"action":[102],"can":[103],"be":[104],"taken":[105],"by":[106],"towards":[109],"customer.":[111]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2018-02-23T00:00:00"}