Process Framework for Subscriber Management and Retention in Nigerian Telecommunication Industry

in the global telecommunication industry. Hence, a dominant approach for subscriber management and retention is churn control, since it is cheaper to retain an existing subscriber than acquiring a new one. Predictive modeling employs the use of data mining techniques to identify patterns and provide a result that a group of subscribers are likely to churn in the near future. However, the effectiveness of subscriber retention strategy in an organization can be further boosted if the reason for churn and the timing of churn can also be predicted. In this paper, we propose a data mining process framework that can be used to predict churn, determine when a subscriber is likely to churn, provides the reason why a subscriber may churn, and recommend appropriate intervention strategy for customer retention using a combination of statistical and machine learning techniques. This experiment is carried out using data from a major telecom operator in Nigeria

Social Differentiation of Inter-word Yod Coalescence in Spoken Nigerian English

This study attempts to track the incidence of inter-word yod coalescence and possibility of its correlation with social factors in Nigerian English. Three hundred and sixty educated Nigerian speakers of English, evenly distributed into social variables of gender, age and social class, provided data for the study. They were guided to voice five utterances and a short passage into digital recording devices. Tokens of yod coalescence produced at different word boundaries were extracted and analysed statistically, using percentages and the univariate Analysis of Variance (ANOVA). The findings reveal a very low usage (3.6%) of inter-word yod coalescence. The process was, however, more prevalent among young speakers and members of high social class who seem to be importing it into the accent. This finding points in the direction of some ongoing innovation in the NigE accent, which possibly suggests the onset of socially conditioned phoneticphonological variation

Design of A Fuzzy Ranking System for Admission Processes in Higher School of Learning

An expert system is a computer program that contains some of the subject-specific knowledge, as well as the knowledge and analytical skills of one or more human experts and reasons with uncertainty and imprecise information. Currently, in Nigeria, there are very few institutions that use computerized admission systems. Most institutions are still using manual process of admission system. However, the major task is to determine whether a candidate is qualified or not based on the ordinary level (0' level) results requirements, the qualifying examination result cut off mark for their course of choice and other determinant factors. In this paper we introduced fuzzy harming distance function into candidates ranking and implemented it with Java Netbean IDE 6.0. The system was used to evaluate candidates' cr'edentials and every other determinant factor for admitting students. The results showed each candidate's chances of admission, while the system minimized the level of subjectivity in decision makin

Application of Fizzy Logic in Decision Making on Student’s academic performance.

Decision making is a knowledge is a knowledge discovery in Fuzzy logic application. Therefore, this paper conceptually defined, explained, and implemented fuzzy logic to the model to system performance, specifically, students’ performance model is studied and the various results generated and the performance chart obtained from overall performance for each year for the consecutive eight years in making decisions for future academic performance are also obtained