VAiRoma: A Visual Analytics System for Making Sense of Places, Times, and Events in Roman History

PROJECT TITLE :

VAiRoma: A Visual Analytics System for Making Sense of Places, Times, and Events in Roman History

ABSTRACT:

Learning and gaining knowledge of Roman history is an area of interest for students and voters at massive. This can be an example of a subject matter with nice sweep (with several interrelated sub-topics over, during this case, a three,00zero year history) that is laborious to grasp by somebody and, in its full detail, is not on the market as a coherent story. During this paper, we tend to propose a visible analytics approach to construct a information driven view of Roman history primarily based on a large collection of Wikipedia articles. Extracting and enabling the discovery of helpful knowledge on events, places, times, and their connections from giant amounts of textual data has forever been a difficult task. To this aim, we introduce VAiRoma, a visual analytics system that couples state-of-the-art text analysis strategies with an intuitive visual interface to assist users create sense of events, places, times, and more importantly, the relationships between them. VAiRoma goes beyond textual content exploration, as it permits users to match, build connections, and externalize the findings all at intervals the visual interface. As a result, VAiRoma allows users to learn and create new knowledge concerning Roman history in an informed method. We have a tendency to evaluated VAiRoma with 16 participants through a user study, with the task being to be told regarding roman piazzas through finding relevant articles and new relationships. Our study results showed that the VAiRoma system allows the participants to find a lot of relevant articles and connections compared to Internet searches and literature search conducted during a roman library. Subjective feedback on VAiRoma was additionally terribly positive. Likewise, we ran 2 case studies that demonstrate how VAiRoma will be used for deeper analysis, allowing the rapid discovery and analysis of a little variety of key documents even when the original assortment contains hundreds of thousands of documents.

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