Poster:Visual Analysis of Stream Texts with Keywords Significance
نویسندگان
چکیده
Stream text collections demand a thorough sophisticated method to explore the massive data and effectively extract valuable information. We propose a force-directed method to dynamically visualize stream text documents. The method captures events as they occur, injects them into the system, and clusters them on-the-fly. Typically, keywords are used to calculate similarity and accordingly steer the clustering results, we propose keywords significance to magnify the importance of certain keywords on-the-go. The user can interactively manipulate the significance of keywords and see the impact on the system. A real dataset example is provided to show the effectiveness of our method.
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