Conference Paper

Visual Analysis of Document Triage Data.

Conference: IMAGAPP & IVAPP 2011 - Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications, Vilamoura, Algarve, Portugal, March 5-7, 2011.
Source: DBLP
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Available from: Fernando Loizides, Aug 26, 2014
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    • "Such interactive clustering approaches go well beyond the standard document analysis [18] [29] [5]. The importance and the need for an interactive visual exploration for text document collection have also been gaining a lot of interest in recent years [13] [16] [15]. Similar to our approach, several studies have actively used node-link diagrams, which visualize documents along with their clusters, allowing users to interactively create a hierarchical structure of topic clusters [27] [31]. "
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    ABSTRACT: Topic modeling has been widely used for analyzing text document collections. Recently, there have been significant advancements in various topic modeling techniques, particularly in the form of probabilistic graphical modeling. State-of-the-art techniques such as Latent Dirichlet Allocation (LDA) have been successfully applied in visual text analytics. However, most of the widely-used methods based on probabilistic modeling have drawbacks in terms of consistency from multiple runs and empirical convergence. Furthermore, due to the complicatedness in the formulation and the algorithm, LDA cannot easily incorporate various types of user feedback. To tackle this problem, we propose a reliable and flexible visual analytics system for topic modeling called UTOPIAN (User-driven Topic modeling based on Interactive Nonnegative Matrix Factorization). Centered around its semi-supervised formulation, UTOPIAN enables users to interact with the topic modeling method and steer the result in a user-driven manner. We demonstrate the capability of UTOPIAN via several usage scenarios with real-world document corpuses such as InfoVis/VAST paper data set and product review data sets.
    Full-text · Article · Dec 2013