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Full-Text Articles in Artificial Intelligence and Robotics
Triaging Twitter Users: An Exploratory Visual Analytics System, Parinaz Nasr Esfahani
Triaging Twitter Users: An Exploratory Visual Analytics System, Parinaz Nasr Esfahani
Electronic Thesis and Dissertation Repository
Twitter is one of the most popular microblogging and social networking services. Many people from a wide range of backgrounds use Twitter to contribute their thoughts on different topics through postings, known as ``tweets”. Analysts collect and analyze tweets to extract knowledge. To rely on tweets, it is crucial to assess Twitter users’ credibility. In recent years, researchers have proposed various techniques, especially data analytics models, for evaluating Twitter users and analyzing their behaviour; however, these techniques do not engage analysts in the process, leading to a lack of understanding and trust in results. In this thesis, an exploratory visual …
Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh
Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh
Electronic Thesis and Dissertation Repository
Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …
A Visual Analytics System For Investigating Multimorbidity Using Supervised Machine Learning, Maede Sadat Nouri
A Visual Analytics System For Investigating Multimorbidity Using Supervised Machine Learning, Maede Sadat Nouri
Electronic Thesis and Dissertation Repository
Patterns of multimorbidity are complex and difficult to summarise using static visualization techniques like tables and charts. We present a visual analytics system with the goal of facilitating the process of making sense of data collected from patients with multimorbidity. The system reveals underlying patterns in the data visually and interactively, which enables users to easily assess both prevalence and correlation estimates of different chronic diseases among multimorbid patients with varying characteristics. To do so, the system uses count-based conditional probability, binary logistic regression, softmax regression and decision tree models to dynamically compute and visualize prevalence and correlation estimates for …