Business Intelligence (BI) relies on Data Warehouse (DW), a historical data repository designed to support the decision making process. Without an effective Data Warehouse, organizations cannot extract the data requir...
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Business Intelligence (BI) and Data Analytics applications depend on an effective ETL (Extract, Transform and Load) process . This paper presents an approach and a Rapid Application Development (RAD) tool to increase ...
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ISBN:
(纸本)9788576693178
Business Intelligence (BI) and Data Analytics applications depend on an effective ETL (Extract, Transform and Load) process . This paper presents an approach and a Rapid Application Development (RAD) tool to increase efficiency and effectiveness of ETL programs development and maintenance. Furthermore, it is also described a controlled experiment conducted in industry to carefully evaluated the efficiency and effectiveness of the tool. The results indicate that our approach can indeed be used as method aimed at improving and speed up ETL process maintenance.
This paper presents an approach to automate the selection and execution of previously indentified test cases for loading procedures in Business Intelligence (BI) environments based on Data Warehouse (DW). To verify an...
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ISBN:
(纸本)189170639X
This paper presents an approach to automate the selection and execution of previously indentified test cases for loading procedures in Business Intelligence (BI) environments based on Data Warehouse (DW). To verify and validate the approach, a unit test framework was developed. The overall goal is achieve data quality improvement. The specific aim is reduce test effort and, consequently, promote test activities in data warehousing process. A controlled experiment evaluation was carried out to investigate the adequacy of the proposed method for data warehouse procedures development. The results of the experiment show that our approach clearly reduces test effort when compared with manual execution of test cases.
In the context of backend development, adopting microservices has brought new challenges to frontend integration, leading to the development of microfrontends. Monolithic frontends go against the principles of microse...
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Information systems that support public sector daily activities generate large data sets. As a large proportion of the data in these data sets are text, Text Mining can play an important role in deriving potentially u...
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Business Intelligence (BI) relies on Data Warehouse (DW), a historical data repository designed to support the decision making process. Without an effective Data Warehouse, organizations cannot extract the data requir...
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Business Intelligence (BI) relies on Data Warehouse (DW), a historical data repository designed to support the decision making process. Without an effective Data Warehouse, organizations cannot extract the data required for information analysis in time to enable more effective strategic, tactical, and operational insights. This paper presents an approach and a Rapid Application Development (RAD) tool to increase efficiency and effectiveness of ETL (Extract, Transform and Load) programs development. An experimental evaluation of the approach is carried out in a controlled experiment that carefully evaluated the efficiency and effectiveness of the tool in an industrial setting. The results indicate that our approach can indeed be used as method aimed at improving ETL process development.
Empathy plays an important role in social interactions, for example, in effective teaching-learning processes in teacher-student relationships, and in the company-client or employee-customer relationships, retaining p...
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Empathy plays an important role in social interactions, for example, in effective teaching-learning processes in teacher-student relationships, and in the company-client or employee-customer relationships, retaining potential partners and providing them with greater satisfaction. In parallel, the computer-Mediated Communication (CMC) support people in their interactions, especially when the interlocutors are geographically distant from one another. In CMC, there are several approaches to promote empathy in social or human computer interactions. However, for this type of communication, a little explored mechanism to gain empathy is the use of the theory of Neurolinguistics that presents the possibility of developing a Preferred Representation System (PRS) for cognition in humans. In this context, this paper presents an experimental evaluation of the NeuroMessenger, a collaborative messenger library that uses Neurolinguistics, Psychometry and Text Mining to promote empathy among interlocutors, from the PRS identification and suggestion of textual matching. The results showed that the performance with the use of NeuroMessenger, in favor of empathy, was higher, as well as there was an evidence statistically significant of the difference between the distribution of grades in the empathy evaluation, in favor of NeuroMessenger. Despite the results are satisfactory, more research on textual matching to gain empathy is needed.
Context: Nowadays, client reviews on social networks can be a great source of knowledge extraction for strategic marketing planning. In the tourism area, opinions given by hotel clients in tourism social networks can ...
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ISBN:
(纸本)9781665445993
Context: Nowadays, client reviews on social networks can be a great source of knowledge extraction for strategic marketing planning. In the tourism area, opinions given by hotel clients in tourism social networks can drive improvements in service. In this context, traditional text mining techniques and new deep learning technologies should be tried out to select the best options for classifying opinions. Objective: Evaluate the performance and quality of the LDA (Latent Dirichlet Allocation), Naives Bayes (NB), Logistic Regression, SVM (Support Vector Machine) and LSTM - Long Short-Term Memory Units algorithms in the task of opinion mining of hotel reviews published on the TripAdvisor hotel booking website. Method: An In Vivo Controlled Experiment (Case Study) to compare the performance of the classifiers by means of accuracy, precision, recall, F1-measure and average training and classification times. Results: The LSTM model presented the best results regarding quality metrics. However, it did not present satisfactory results regarding processing time. Conclusion: The LSTM classifier had clearly superior performance when compared to the other evaluated ones. On the other hand, its average training and classification times greater than the others classifiers considered.
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