Matches in SemOpenAlex for { <https://semopenalex.org/work/W2955107153> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W2955107153 abstract "Nowadays, the telecom industries are going through a big problem that is customer churn. Recently, the market for mobile telecom industry has to change very promptly and there is a ferocious competition between them. Most of the telecom companies always concentrate on to obtain a new customer, but they do not pay too much attention to their existing customer. That’s why the company tries to find out that customers those have tendency to switch over in future. The information picked up from telecom industry to find out the logic of churning and try to solve those problems. The company targets those customers with a special program. The aim of this paper is to predict the customer churn for telecom industries using machine learning techniques namely Logistic Regression, Naive Bayes and Decision Trees. In telecom industries, the principal objective of churning is to accurately calculate the customer survival and customer risk capabilities to gather the entire information of churn over the client residency. This paper summarizes the technique of predicting the churn so have a wide understanding of the customer churn. So that the telecom industries are aware in advance the big hazard customer and rectify their services to repeal the decision of churn. Customer profiling for predicting the customer who have churned in advance are also analyzed." @default.
- W2955107153 created "2019-07-12" @default.
- W2955107153 creator A5048995879 @default.
- W2955107153 creator A5053733870 @default.
- W2955107153 creator A5061132370 @default.
- W2955107153 creator A5069395230 @default.
- W2955107153 creator A5074544429 @default.
- W2955107153 date "2019-01-01" @default.
- W2955107153 modified "2023-09-26" @default.
- W2955107153 title "Adaptive Customer Profiling for Telecom Churn Prediction Using Computation Intelligence" @default.
- W2955107153 cites W1874894429 @default.
- W2955107153 cites W1973004077 @default.
- W2955107153 cites W2010718781 @default.
- W2955107153 cites W2204900049 @default.
- W2955107153 cites W2321670847 @default.
- W2955107153 cites W2460450520 @default.
- W2955107153 cites W2563747947 @default.
- W2955107153 cites W2597939835 @default.
- W2955107153 doi "https://doi.org/10.1007/978-981-13-8581-0_6" @default.
- W2955107153 hasPublicationYear "2019" @default.
- W2955107153 type Work @default.
- W2955107153 sameAs 2955107153 @default.
- W2955107153 citedByCount "0" @default.
- W2955107153 crossrefType "book-chapter" @default.
- W2955107153 hasAuthorship W2955107153A5048995879 @default.
- W2955107153 hasAuthorship W2955107153A5053733870 @default.
- W2955107153 hasAuthorship W2955107153A5061132370 @default.
- W2955107153 hasAuthorship W2955107153A5069395230 @default.
- W2955107153 hasAuthorship W2955107153A5074544429 @default.
- W2955107153 hasConcept C101276457 @default.
- W2955107153 hasConcept C111919701 @default.
- W2955107153 hasConcept C116537 @default.
- W2955107153 hasConcept C12267149 @default.
- W2955107153 hasConcept C131357253 @default.
- W2955107153 hasConcept C140781008 @default.
- W2955107153 hasConcept C144133560 @default.
- W2955107153 hasConcept C145236788 @default.
- W2955107153 hasConcept C154945302 @default.
- W2955107153 hasConcept C161664118 @default.
- W2955107153 hasConcept C162324750 @default.
- W2955107153 hasConcept C162853370 @default.
- W2955107153 hasConcept C187191949 @default.
- W2955107153 hasConcept C2780378061 @default.
- W2955107153 hasConcept C41008148 @default.
- W2955107153 hasConcept C43595421 @default.
- W2955107153 hasConcept C52001869 @default.
- W2955107153 hasConcept C56961345 @default.
- W2955107153 hasConcept C76155785 @default.
- W2955107153 hasConceptScore W2955107153C101276457 @default.
- W2955107153 hasConceptScore W2955107153C111919701 @default.
- W2955107153 hasConceptScore W2955107153C116537 @default.
- W2955107153 hasConceptScore W2955107153C12267149 @default.
- W2955107153 hasConceptScore W2955107153C131357253 @default.
- W2955107153 hasConceptScore W2955107153C140781008 @default.
- W2955107153 hasConceptScore W2955107153C144133560 @default.
- W2955107153 hasConceptScore W2955107153C145236788 @default.
- W2955107153 hasConceptScore W2955107153C154945302 @default.
- W2955107153 hasConceptScore W2955107153C161664118 @default.
- W2955107153 hasConceptScore W2955107153C162324750 @default.
- W2955107153 hasConceptScore W2955107153C162853370 @default.
- W2955107153 hasConceptScore W2955107153C187191949 @default.
- W2955107153 hasConceptScore W2955107153C2780378061 @default.
- W2955107153 hasConceptScore W2955107153C41008148 @default.
- W2955107153 hasConceptScore W2955107153C43595421 @default.
- W2955107153 hasConceptScore W2955107153C52001869 @default.
- W2955107153 hasConceptScore W2955107153C56961345 @default.
- W2955107153 hasConceptScore W2955107153C76155785 @default.
- W2955107153 hasLocation W29551071531 @default.
- W2955107153 hasOpenAccess W2955107153 @default.
- W2955107153 hasPrimaryLocation W29551071531 @default.
- W2955107153 hasRelatedWork W1971902502 @default.
- W2955107153 hasRelatedWork W1978025562 @default.
- W2955107153 hasRelatedWork W2131606248 @default.
- W2955107153 hasRelatedWork W2142242608 @default.
- W2955107153 hasRelatedWork W2368747170 @default.
- W2955107153 hasRelatedWork W2385901836 @default.
- W2955107153 hasRelatedWork W2508015119 @default.
- W2955107153 hasRelatedWork W2898975593 @default.
- W2955107153 hasRelatedWork W2955107153 @default.
- W2955107153 hasRelatedWork W658427728 @default.
- W2955107153 isParatext "false" @default.
- W2955107153 isRetracted "false" @default.
- W2955107153 magId "2955107153" @default.
- W2955107153 workType "book-chapter" @default.