2,691 research outputs found

    Collaborative-demographic hybrid for financial: product recommendation

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    Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsDue to the increased availability of mature data mining and analysis technologies supporting CRM processes, several financial institutions are striving to leverage customer data and integrate insights regarding customer behaviour, needs, and preferences into their marketing approach. As decision support systems assisting marketing and commercial efforts, Recommender Systems applied to the financial domain have been gaining increased attention. This thesis studies a Collaborative- Demographic Hybrid Recommendation System, applied to the financial services sector, based on real data provided by a Portuguese private commercial bank. This work establishes a framework to support account managers’ advice on which financial product is most suitable for each of the bank’s corporate clients. The recommendation problem is further developed by conducting a performance comparison for both multi-output regression and multiclass classification prediction approaches. Experimental results indicate that multiclass architectures are better suited for the prediction task, outperforming alternative multi-output regression models on the evaluation metrics considered. Withal, multiclass Feed-Forward Neural Networks, combined with Recursive Feature Elimination, is identified as the topperforming algorithm, yielding a 10-fold cross-validated F1 Measure of 83.16%, and achieving corresponding values of Precision and Recall of 84.34%, and 85.29%, respectively. Overall, this study provides important contributions for positioning the bank’s commercial efforts around customers’ future requirements. By allowing for a better understanding of customers’ needs and preferences, the proposed Recommender allows for more personalized and targeted marketing contacts, leading to higher conversion rates, corporate profitability, and customer satisfaction and loyalty

    Towards Automated Experiments in Software Intensive Systems

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    Context: Delivering software that has value to customers is a primary concern of every software company. One of the techniques to continuously validate and deliver value in online software systems is the use of controlled experiments. The time cost of each experiment iteration, the increasing growth in the development organization to run experiments and the need for a more automated and systematic approach is leading companies to look for different techniques to automate the experimentation process. Objective: The overall objective of this thesis is to analyze how to automate different types of experiments and how companies can support and optimize their systems through automated experiments. This thesis explores the topic of automated online experiments from the perspectives of the software architecture, the algorithms for the experiment execution and the experimentation process, and focuses on two main application domains: the online and the embedded systems domain. Method: To achieve the objective, we conducted this research in close collaboration with industry using a combination of different empirical research methods: case studies, literature reviews, simulations and empirical evaluations. Results and conclusions: This thesis provides five main results. First, we propose an architecture framework for automated experimentation that can be used with different types of experimental designs in both embedded systems and web-facing systems. Second, we identify the key challenges faced by embedded systems companies when adopting controlled experimentation and we propose a set of strategies to address these challenges. Third, we develop a new algorithm for online experiments. Fourth, we identify restrictions and pitfalls of different algorithms for automating experiments in industry and we propose a set of guidelines to help practitioners select a technique that minimizes the occurrence of these pitfalls. Fifth, we propose a new experimentation process to capture the details of a trustworthy experimentation process that can be used as basis for an automated experimentation process. Future work: In future work, we plan to investigate how embedded systems can incorporate experiments in their development process without compromising existing real-time and safety requirements. We also plan to analyze the impact and costs of automating the different parts of the experimentation process

    On Experimentation in Software-Intensive Systems

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    Context: Delivering software that has value to customers is a primary concern of every software company. Prevalent in web-facing companies, controlled experiments are used to validate and deliver value in incremental deployments. At the same that web-facing companies are aiming to automate and reduce the cost of each experiment iteration, embedded systems companies are starting to adopt experimentation practices and leverage their activities on the automation developments made in the online domain. Objective: This thesis has two main objectives. The first objective is to analyze how software companies can run and optimize their systems through automated experiments. This objective is investigated from the perspectives of the software architecture, the algorithms for the experiment execution and the experimentation process. The second objective is to analyze how non web-facing companies can adopt experimentation as part of their development process to validate and deliver value to their customers continuously. This objective is investigated from the perspectives of the software development process and focuses on the experimentation aspects that are distinct from web-facing companies. Method: To achieve these objectives, we conducted research in close collaboration with industry and used a combination of different empirical research methods: case studies, literature reviews, simulations, and empirical evaluations. Results: This thesis provides six main results. First, it proposes an architecture framework for automated experimentation that can be used with different types of experimental designs in both embedded systems and web-facing systems. Second, it proposes a new experimentation process to capture the details of a trustworthy experimentation process that can be used as the basis for an automated experimentation process. Third, it identifies the restrictions and pitfalls of different multi-armed bandit algorithms for automating experiments in industry. This thesis also proposes a set of guidelines to help practitioners select a technique that minimizes the occurrence of these pitfalls. Fourth, it proposes statistical models to analyze optimization algorithms that can be used in automated experimentation. Fifth, it identifies the key challenges faced by embedded systems companies when adopting controlled experimentation, and we propose a set of strategies to address these challenges. Sixth, it identifies experimentation techniques and proposes a new continuous experimentation model for mission-critical and business-to-business. Conclusion: The results presented in this thesis indicate that the trustworthiness in the experimentation process and the selection of algorithms still need to be addressed before automated experimentation can be used at scale in industry. The embedded systems industry faces challenges in adopting experimentation as part of its development process. In part, this is due to the low number of users and devices that can be used in experiments and the diversity of the required experimental designs for each new situation. This limitation increases both the complexity of the experimentation process and the number of techniques used to address this constraint

    Recommended Practices for the Implementation of Wind Power Forecasting Solutions : Part 3: Evaluation of Forecasts and Forecast Solutions

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    This is the third part of a series of three recommended practice documents that deal with the development and operation of forecasting solutions in the power market
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