{"id":"https://openalex.org/W4391237251","doi":"https://doi.org/10.1109/ictacs59847.2023.10390329","title":"Telecom Sector Churn Prediction Using Decision Tree and Random Forest Models","display_name":"Telecom Sector Churn Prediction Using Decision Tree and Random Forest Models","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4391237251","doi":"https://doi.org/10.1109/ictacs59847.2023.10390329"},"language":"en","primary_location":{"id":"doi:10.1109/ictacs59847.2023.10390329","doi":"https://doi.org/10.1109/ictacs59847.2023.10390329","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ictacs59847.2023.10390329","pdf_url":null,"source":{"id":"https://openalex.org/S4363608123","display_name":"International Conference on Technological Advancements in Computational Sciences (ICTACS)","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":"2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5111118630","display_name":"Swasti Arya","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I74885063","display_name":"Sharda University","ror":"https://ror.org/03b6ffh07","country_code":"IN","type":"education","lineage":["https://openalex.org/I74885063"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Swasti Arya","raw_affiliation_strings":["Sharda University,Department of Computer Science and Engineering,Uttar Pradesh,India","Department of Computer Science and Engineering, Sharda University, Uttar Pradesh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sharda University,Department of Computer Science and Engineering,Uttar Pradesh,India","institution_ids":["https://openalex.org/I74885063"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Sharda University, Uttar Pradesh, India","institution_ids":["https://openalex.org/I74885063"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093790895","display_name":"Yuvraj Harshvardhan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I74885063","display_name":"Sharda University","ror":"https://ror.org/03b6ffh07","country_code":"IN","type":"education","lineage":["https://openalex.org/I74885063"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Yuvraj Harshvardhan","raw_affiliation_strings":["Sharda University,Department of Computer Science and Engineering,Uttar Pradesh,India","Department of Computer Science and Engineering, Sharda University, Uttar Pradesh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sharda University,Department of Computer Science and Engineering,Uttar Pradesh,India","institution_ids":["https://openalex.org/I74885063"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Sharda University, Uttar Pradesh, India","institution_ids":["https://openalex.org/I74885063"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101435359","display_name":"Priyanka Tyagi","orcid":"https://orcid.org/0000-0003-4290-5361","observed_orcids":["https://orcid.org/0000-0003-4290-5361","https://orcid.org/0009-0008-0162-6976"]},"institutions":[{"id":"https://openalex.org/I74885063","display_name":"Sharda University","ror":"https://ror.org/03b6ffh07","country_code":"IN","type":"education","lineage":["https://openalex.org/I74885063"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Priyanka Tyagi","raw_affiliation_strings":["Sharda University,Department of Computer Science and Engineering,Uttar Pradesh,India","Department of Computer Science and Engineering, Sharda University, Uttar Pradesh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sharda University,Department of Computer Science and Engineering,Uttar Pradesh,India","institution_ids":["https://openalex.org/I74885063"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Sharda University, Uttar Pradesh, India","institution_ids":["https://openalex.org/I74885063"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74885063"],"apc_list":null,"apc_paid":null,"fwci":1.4322,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.83316549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"106","last_page":"111"},"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/T10154","display_name":"Customer Service Quality and Loyalty","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/customer-churn-prediction","display_name":"customer churn prediction","score":0.9919999837875366},{"id":"https://openalex.org/keywords/telecommunications-industry","display_name":"telecommunications industry","score":0.8080000281333923},{"id":"https://openalex.org/keywords/mobile-network-operators","display_name":"mobile operators","score":0.6570000052452087},{"id":"https://openalex.org/keywords/decision-tree","display_name":"decision tree","score":0.6990000009536743},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8529999852180481},{"id":"https://openalex.org/keywords/customer-retention","display_name":"customer retention","score":0.9520000219345093},{"id":"https://openalex.org/keywords/subscription-cancellation","display_name":"subscription cancellation","score":0.7300000190734863},{"id":"https://openalex.org/keywords/customer-service","display_name":"customer service","score":0.414000004529953}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7246524095535278},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.7206863164901733},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5836527943611145},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.43787115812301636},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.4213125705718994},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26412343978881836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23932158946990967},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09096664190292358},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictacs59847.2023.10390329","doi":"https://doi.org/10.1109/ictacs59847.2023.10390329","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ictacs59847.2023.10390329","pdf_url":null,"source":{"id":"https://openalex.org/S4363608123","display_name":"International Conference on Technological Advancements in Computational Sciences (ICTACS)","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":"2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W168242428","https://openalex.org/W2074780813","https://openalex.org/W2490017371","https://openalex.org/W2939289155","https://openalex.org/W3024539486","https://openalex.org/W3130989307","https://openalex.org/W3142156319","https://openalex.org/W4200444575","https://openalex.org/W4221065845","https://openalex.org/W4285815530","https://openalex.org/W4376645753"],"related_works":["https://openalex.org/W4400490996","https://openalex.org/W4293791119","https://openalex.org/W4391576473","https://openalex.org/W7220038669","https://openalex.org/W7220304057","https://openalex.org/W3012817390","https://openalex.org/W4323323652","https://openalex.org/W6968058422","https://openalex.org/W2985582295","https://openalex.org/W4407057772"],"abstract_inverted_index":{"Telecommunication":[0],"sector":[1],"is":[2,29,80],"an":[3],"important":[4],"industry":[5],"in":[6,16,168],"upcoming":[7],"developing":[8],"countries.":[9],"The":[10,159],"Tech":[11],"progress,":[12],"the":[13,17,22,25,154,173],"rapid":[14],"increase":[15],"number":[18],"of":[19,24,35,56,97,111,157],"operators":[20],"raising":[21],"competition":[23],"industry.":[26,175],"Customer":[27],"churn":[28,171],"Leading":[30],"as":[31,39],"one":[32],"biggest":[33],"problem":[34],"mobile":[36],"phone":[37],"companies":[38,177],"it":[40,150],"can":[41,51,178],"have":[42],"a":[43,54,61,64,73,76,81,108],"significant":[44],"impact":[45],"on":[46],"sales":[47],"and":[48,124,145],"revenue.":[49],"Loss":[50],"happen":[52],"for":[53],"variety":[55],"reasons,":[57],"including":[58,90],"switching":[59,91],"to":[60,67,87,129,134,152,182],"competitor,":[62],"canceling":[63],"subscription":[65,95],"due":[66],"bad":[68],"customer":[69,99,170],"service,":[70,100],"or":[71,101],"severing":[72],"relationship":[74],"with":[75,107],"company":[77],"because":[78,86,96,110],"there":[79],"link.":[82],"Churn":[83],"might":[84],"be":[85],"various":[88],"factors,":[89],"other":[92],"company,":[93],"cancelling":[94],"poor":[98],"maybe":[102],"not":[103],"continuing":[104],"all":[105],"contact":[106],"brand":[109],"insufficient":[112],"touch-points.":[113],"To":[114],"meet":[115],"this":[116,138,180],"challenge,":[117],"predictive":[118],"modeling":[119],"tools":[120],"like":[121],"decision":[122,143],"trees":[123,144],"random":[125,146,164],"forest":[126],"are":[127,166,190],"used":[128],"identify":[130],"customers":[131,188],"most":[132],"likely":[133],"lose":[135],"customers.":[136],"In":[137],"study":[139],"we":[140],"examine":[141],"how":[142],"forests":[147,165],"perform":[148],"when":[149],"comes":[151],"predicting":[153],"communication":[155],"skills":[156],"users.":[158],"research":[160],"findings":[161],"suggest":[162],"that":[163],"effective,":[167],"forecasting":[169],"within":[172],"communications":[174],"Telecommunications":[176],"leverage":[179],"information":[181],"develop":[183],"strategies":[184],"aimed":[185],"at":[186],"retaining":[187],"who":[189],"considering":[191],"leaving.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2024-01-26T00:00:00"}