Churn Prediction in Telecommunication Industry Using Rough Set Approach

Amin, Adnan; Shehzad, Saeed; Khan, Changez; Ali, Imtiaz; Anwar, Sajid

doi:10.1007/978-3-319-10774-5_8

Cited by 36 publications

(40 citation statements)

References 23 publications

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“…An illustration of typical data acquisition and analysis for customer churn is given by Almana et al along with a conclusion regarding the convenience of using rule‐based techniques. Furthermore, Amin et al introduce rough sets for customer churn analysis and argue that their approach is powerful for constructing rules in the CSP domain. We also consider rough sets for extracting knowledge structures, particularly those that have a form of rules addressing the type of information typical in the CSP domain.…”

Section: Related Workmentioning

confidence: 99%

Extending a communication service provider's operations management based on knowledge granules and aspects derived from imperfect information

Dragun

Bogunović

2019

Int J Communication

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The core of a communication service provider's business revolves around servicerelated operations management, usually relying strongly on expert knowledge built inside the company. Knowledge representation in this environment inevitably requires addressing various domains. Team members working on common tasks bring domain diversity to their teams due to their various ontological areas of expertise. All team members must attain an acceptable level of knowledge regarding other domains to reach a team's desired level of effectiveness. This paper provides a novel way of linking divergent domain ontologies to facilitate and enrich service management in the communication service provider environment. The typical service provider infrastructure offers an extensive source of information for deriving knowledge regarding services, but the information is generally imperfect, inconsistent, and incomplete. Introducing a granular approach based on rough sets applicable to this imperfect information enables fractional management, which together with multiaspect formalisms enables the derivation of the specificity of a certain domain from a common source of knowledge without interference from other domains. A case study illustrates the implementation of an intelligent communication service and network management system based on the contexts used for assisting service strategies. The implementation empirically justifies the proposed approach.KEYWORDS aspects, imperfect information, knowledge granules, knowledge management, service operations management 1 | INTRODUCTION Communication service providers (CSPs) attempt to incorporate many disciplines into their daily service providing processes to differentiate themselves in the market. This incorporation involves broadening the set of standard telecomrelated domains by introducing new domains necessary to produce new content and to enrich existing portfolios. The final goal of these activities is to improve the CSP's service quality. However, despite many advantages of a multidisciplinary approach, stemming mostly from the fact that diversity results in greater versatility when providing services, substantial challenges exist under these conditions. Because introducing various disciplines requires bringing in experts from those disciplines to work together to provide the related services, functional teams covering all necessary domains

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Section: Related Workmentioning

confidence: 99%

Extending a communication service provider's operations management based on knowledge granules and aspects derived from imperfect information

Dragun

Bogunović

2019

Int J Communication

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“…Adnan Amin et al, 2015 [27] discretization is a action of accumulating the quality's abstracts based on the bent cuts and the amaranthine factors, alteration over into detached attributes. There may exists such concealed article which can't coordinate with the guidelines or it can increment computational cost that hinder the AI procedure, so cut and discretization techniques are utilized so as to get high caliber of characterization.…”

Section: Ntelecom Industry Analysis Using Machine Learning Processesmentioning

confidence: 99%

Churn rate prediction in Telecommunication systems

R*,

Ganesh

2019

IJEAT

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The broad view of chum rate measures the amount of individuals or items comes out of a collective group over a predefined time period. Many challenges linked with the churn rates in the telecom industry rise in increasing competition with the elimination of switching costs. The customer loyalty over the telecom industry exists along with the service provider struggling to offer improved services with the lower cost. Many author reviews depends on the churn rate prediction in the field of telecommunication sector discussed with the paper. The paper talk about an idea related with an application of churn rate for the technical review.

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“…Compared with typically favored structured parametric models (logit, probit, or hazard models), machine learning literature have introduced many models with good predictive ability, such as support vector machine [24], multivariate decision tree [26]. However, most of these models focus on a binary classification problem to predict whether a customer would grow into a high-value customer [27,28], and rarely study the regression prediction of customer value. In fact, the scalar value of customer value is gradually becoming the focus of enterprises' attention.…”

Section: Value Prediction Modelmentioning

confidence: 99%

A Time-aware Multi-task Learning Model for Customer Value Prediction in Civil Aviation

2019

Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering

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The precise prediction of customer value is essential for any successful dynamic customer relationship management (CRM) system. It is also the key for the company to maximizing customer returns. In this research, we concentrate on two main aspects of the work in civil aviation field. Firstly, a reasonable value model is the premise of this prediction issue. Therefore, we propose a parametric customer value model RFUM to estimate customer value in civil aviation. It evaluates customer value from four different attributes and then presents customer value by the weight of the attributes. Secondly, Time-aware Multi-task Value Prediction (TMVP) model is proposed to predict the future value of customer. It employs two supervisory signals of purchase propensity and customer value to better train a specific neural network to automatically learn features. Experiments demonstrate that the RFUM model can more accurately measure the value of customer in civil aviation market and the TMVP model can achieve a more precise regression prediction result. In addition, we also find that increasing the time of a single calculation window can improve the performance markedly.

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Churn Prediction in Telecommunication Industry Using Rough Set Approach

Cited by 36 publications

References 23 publications

Extending a communication service provider's operations management based on knowledge granules and aspects derived from imperfect information

Extending a communication service provider's operations management based on knowledge granules and aspects derived from imperfect information

Churn rate prediction in Telecommunication systems

A Time-aware Multi-task Learning Model for Customer Value Prediction in Civil Aviation

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