3 research outputs found

    Twitter Analysis to Predict the Satisfaction of Saudi Telecommunication Companies’ Customers

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    The flexibility in mobile communications allows customers to quickly switch from one service provider to another, making customer churn one of the most critical challenges for the data and voice telecommunication service industry. In 2019, the percentage of post-paid telecommunication customers in Saudi Arabia decreased; this represents a great deal of customer dissatisfaction and subsequent corporate fiscal losses. Many studies correlate customer satisfaction with customer churn. The Telecom companies have depended on historical customer data to measure customer churn. However, historical data does not reveal current customer satisfaction or future likeliness to switch between telecom companies. Current methods of analysing churn rates are inadequate and faced some issues, particularly in the Saudi market. This research was conducted to realize the relationship between customer satisfaction and customer churn and how to use social media mining to measure customer satisfaction and predict customer churn. This research conducted a systematic review to address the churn prediction models problems and their relation to Arabic Sentiment Analysis. The findings show that the current churn models lack integrating structural data frameworks with real-time analytics to target customers in real-time. In addition, the findings show that the specific issues in the existing churn prediction models in Saudi Arabia relate to the Arabic language itself, its complexity, and lack of resources. As a result, I have constructed the first gold standard corpus of Saudi tweets related to telecom companies, comprising 20,000 manually annotated tweets. It has been generated as a dialect sentiment lexicon extracted from a larger Twitter dataset collected by me to capture text characteristics in social media. I developed a new ASA prediction model for telecommunication that fills the detected gaps in the ASA literature and fits the telecommunication field. The proposed model proved its effectiveness for Arabic sentiment analysis and churn prediction. This is the first work using Twitter mining to predict potential customer loss (churn) in Saudi telecom companies, which has not been attempted before. Different fields, such as education, have different features, making applying the proposed model is interesting because it based on text-mining

    RESTful Web Services Development with a Model-Driven Engineering Approach

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    A RESTful web service implementation requires following the constrains inherent to Representational State Transfer (REST) architectural style, which, being a non-trivial task, often leads to solutions that do not fulfill those requirements properly. Model-driven techniques have been proposed to improve the development of complex applications. In model-driven software development, software is not implemented manually based on informal descriptions, but partial or completely generated from formal models derived from metamodels. A model driven approach, materialized in a domain specific language that integrates the OpenAPI specification, an emerging standard for describing REST services, allows developers to use a design first approach in the web service development process, focusing in the definition of resources and their relationships, leaving the repetitive code production process to the automation provided by model-driven engineering techniques. This also allows to shift the creative coding process to the resolution of the complex business rules, instead of the tiresome and error-prone create, read, update, and delete operations. The code generation process covers the web service flow, from the establishment and exposure of the endpoints to the definition of database tables.A implementação de serviços web RESTful requer que as restrições inerentes ao estilo arquitetónico “Representational State Transfer” (REST) sejam cumpridas, o que, sendo usualmente uma tarefa não trivial, geralmente leva a soluções que não atendem a esses requisitos adequadamente. Técnicas orientadas a modelos têm sido propostas para melhorar o desenvolvimento de aplicações complexas. No desenvolvimento de software orientado a modelos, o software não é implementado manualmente com base em descrições informais, mas parcial ou completamente gerado a partir de modelos formais derivados de meta-modelos. Uma abordagem orientada a modelos, materializada através de uma linguagem específica do domínio que integra a especificação OpenAPI, um padrão emergente para descrever serviços REST, permite aos desenvolvedores usar uma primeira abordagem de design no processo de desenvolvimento de serviços da Web, concentrando-se na definição dos recursos e das suas relações, deixando o processo de produção de código repetitivo para a automação fornecida por técnicas de engenharia orientadas a modelos. Isso também permite focar o processo de codificação criativo na resolução e implementação das regras de negócios mais complexas, em vez de nas operações mais repetitivas e propensas a erros: criação, leitura, atualização e remoção de dados. O processo de geração de código abrange o fluxo do serviço web desde o estabelecimento e exposição dos caminhos para os serviços disponíveis até à definição de tabelas de base de dados

    Minimising mathematical anxiety in teaching mathematics and assessing student’s work

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    This paper builds up a theoretical perspective and supports a possibility of creating a special assessment environment for students, where mathematical knowledge and understanding can be assessed with a reduced number of external psychological factors that may affect such assessment. A concept of a zone with minimal effect of anxiety is introduced and described. Students’ successful work on extending the zone by means of a carefully selected chain of questions, where some questions only are part of a real assessment, allows students to reconsider their attitudes towards mathematics and assist teachers to identify some students’ main learning difficulties as of psychological character. Further suggestions about developing and investigating special assessment environments are outlined and discussed
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