![]() The brachial plexus is a complex network of peripheral nerves that enables sensing from and control of the movements of the arms and hand. Finally, we demonstrate the effectiveness of ICE with three real-world datasets from different domains. To support comparison at multiple levels, ICE employs the unit visualization technique, and we further explore the design space of unit visualizations for event sequence comparison tasks. More specifically, ICE incorporates a multi-level matrix-based visualization for browsing the entire dataset based on the prefixes and suffixes of sequences. This paper presents, ICE, an interactive visualization that allows analysts to explore an event sequence dataset, and identify promising sets of event sequences to compare at both the pattern and sequence levels. However, analysts often face two challenges: they may not always know which sets of event sequences in the data are useful to compare, and the comparison needs to be achieved at different granularity, due to the volume and complexity of the data. These methods are presented within CroP, a data visualization tool with coordinated multiple views aimed at the analysis of biological datasets.Ĭomparative analysis of event sequence data is essential in many application domains, such as website design and medical care. Through interactive exploration, we demonstrate how these methods can be used to analyze and identify the main agents at the source of significant instances in three biological datasets. The proposed addition of visual elements to the model includes temporal glyphs and a supporting timeline graph which help discover and better understand temporal patterns across complex datasets. In our implementation we introduce Time Paths, a force-directed layout that can dynamically transform the original model to not only smoothen the transitions between time points, but also reduce visual noise in favor of portraying overall patterns. In this paper, we further explore time-series functionally and aesthetically by presenting an interactive and parameter-based implementation of the Time Curves model, complemented with addition of supporting visualizations and data analysis methods. Visualization has shown to be a valuable tool in the analysis of large and complex temporal datasets, aided by the emergence of new models such as Time Curves, which distorts timelines to position time points based on their similarity with each other, reflecting changes in the data over time. Based on the feedback provided by the analysts, we could conclude that ATOVis is an efficient and effective tool in detecting specific patterns of fraud which can improve the analysts’ work. ![]() We also validate our tool through user testing, with experts in fraud detection and experts from other fields of data science. In particular, the present paper incorporates: a task abstraction for detecting a specific financial fraud pattern – ATO two models for the visualisation of ATO and a multiscale timeline to enable an overview of the data. ATOVis focuses on applying visualisation techniques to the Finance domain, specifically e-commerce, contributing to the state-of-the-art as the first visualisation tool primarily specialised in Account Takeover (ATO) patterns. We aim to ease and accelerate fraud detection by providing an overview of specific patterns within the data, and enabling details on demand. To aid in the inspection of fraudulent activities, we develop ATOVis – a visualisation tool that enables a fast analysis and detection of suspicious behaviours. However, this type of inspection is laborious, time-consuming, and may be of little use for the analysis and overview of complex transactional data. Nowadays, experts in charge base their analysis on tabular data, usually presented in spreadsheets and seldom supplemented with simple visualisations. It is a task of high responsibility and, therefore, an important phase of the decision-making chain. Fraud detection is related to the suppression of possible financial losses for institutions and their clients.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |