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document visualization: an overview of current research

WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS 2014年第1期6卷 19-36页

作者： Gan, Qihong Zhu, Min Li, Mingzhao Liang, Ting Cao, Yu Zhou, Baoyao Sichuan Univ Coll Comp Sci Vis Comp Lab Chengdu Sichuan Peoples R China EMC Labs China Beijing Peoples R China

As the number of sources and quantity of document information explodes, efficient and intuitive visualization tools are desperately needed to assist users in understanding the contents and features of a document, while discovering hidden information. This overview introduces fundamental concepts of and designs for document visualization, a number of representative methods in the field, and challenges as well as promising directions of future development. The focus is on explaining the rationale and characteristics of representative document visualization methods for each category. A discussion of the limitations of our classification and a comparison of reviewed methods are presented at the end. This overview also aims to point out theoretical and practical challenges in document visualization. (C) 2013 Wiley Periodicals, Inc.

关键词： document document visualization information visualization interactive graphics

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Sequential document visualization

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2007年第6期13卷 1208-1215页

作者： Mao, Yi Dillon, Joshua V. Lebanon, Guy Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA Purdue Univ Sch Elect & Comp Engn Dept Stat W Lafayette IN 47907 USA

documents and other categorical valued time series are often characterized by the frequencies of short range sequential patterns such as n-grams. This representation converts sequential data of varying lengths to high dimensional histogram vectors which are easily modeled by standard statistical models. Unfortunately, the histograrn representation ignores most of the medium and long range sequential dependencies making it unsuitable for visualizing sequential data. We present a novel framework for sequential visualization of discrete categorical time series based on the idea of local statistical modeling. The framework embeds categorical time series as smooth curves in the multinomial simplex summarizing the progression of sequential trends. We discuss several visualization techniques based on the above framework and demonstrate their usefulness for document visualization.

关键词： document visualization multi-resolution analysis local fitting

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Sequential document visualization Based on Hierarchical Parametric Histogram Curves

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Tsinghua Science and Technology 2012年第4期17卷 409-418页

作者： Haidong Chen Guizhen Wang Dichao Peng Wuheng Zuo Wei Chen State Key Lab of CAD&CG Zhejiang UniversityHangzhou 310058China Zhijiang College of Zhejiang University of Technology Hangzhou 310024China

Recently, sequential document visualization has attracted much attention for its superior capability in depicting the sequential semantic progression in a single document. However, existing methods commonly take abstractive visual forms such as texts, numbers, and glyphs, and require much user expertise for document exploration. In this paper we propose a sequential visualization to represent a single document with a two- dimensional picture-based storyline, which semantically enhances the comprehension of textual information. We introduce a new parametric modeling approach called the Hierarchical Parametric Histogram Curve （HPHC）, which encodes the statistical progression locally and adaptively. By transforming an HPHC into the two-dimensional space with a new locality-preserving embedding algorithm, we create a mapping from points along the curve to descriptive pictures and generate the visualization result. The new representation expresses the primary content with a graphical form, and allows for efficient multi-resolution and focus＋context exploration in a long document. Our approach compares favorably with previous work in that it is more intuitive and requires less user expertise. Informal evaluation shows that it is useful in quick document browsing, communication, and understanding, especially for people with low literacy skills.

关键词： document visualization sequential document visualization pictorial communication histogram curve

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document analysis and visualization with zero-inflated poisson

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DATA MINING AND KNOWLEDGE DISCOVERY 2009年第1期19卷 1-23页

作者： Alvarez, Dora Hidalgo, Hugo CICESE Ensenada 22860 Baja California Mexico

Data visualization is aimed at obtaining a graphic representation of high dimensional information. A data projection over a lower dimensional space is pursued, looking for some structure on the projections. Among the several data projection based methods available, the Generative Topographic Mapping (GTM) has become an important probabilistic framework to model data. The application to document data requires a change in the original (Gaussian) model in order to consider binary or multinomial variables. There have been several modifications on GTM to consider this kind of data, but the resulting latent projections are all scattered on the visualization plane. A document visualization method is proposed in this paper, based on a generative probabilistic model consisting of a mixture of Zero-inflated Poisson distributions. The performance of the method is evaluated in terms of cluster forming for the latent projections with an index based on Fisher's classifier, and the topology preservation capability is measured with the Sammon's stress error. A comparison with the GTM implementation with Gaussian, multinomial and Poisson distributions and with a Latent Dirichlet model is presented, observing a greater performance for the proposed method. A graphic presentation of the projections is also provided, showing the advantage of the developed method in terms of visualization and class separation. A detailed analysis of some documents projected on the latent representation showed that most of the documents appearing away from the corresponding cluster could be identified as outliers.

关键词： document visualization Zero-inflated Poisson Generative model

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VADIS: A Visual Analytics Pipeline for Dynamic document Representation and Information-Seeking

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2025年第1期31卷 1312-1321页

作者： Qiu, Rui Tu, Yamei Yen, Po -Yin Shen, Han -Wei Ohio State Univ Columbus OH 43210 USA Washington Univ Sch Med St Louis MO USA

In the biomedical domain, visualizing the document embeddings of an extensive corpus has been widely used in information-seeking tasks. However, three key challenges with existing visualizations make it difficult for clinicians to find information efficiently. First, the document embeddings used in these visualizations are generated statically by pretrained language models, which cannot adapt to the user's evolving interest. Second, existing document visualization techniques cannot effectively display how the documents are relevant to users' interest, making it difficult for users to identify the most pertinent information. Third, existing embedding generation and visualization processes suffer from a lack of interpretability, making it difficult to understand, trust and use the result for decision-making. In this paper, we present a novel visual analytics pipeline for user-driven document representation and iterative information seeking (VADIS). VADIS introduces a prompt-based attention model (PAM) that generates dynamic document embedding and document relevance adjusted to the user's query. To effectively visualize these two pieces of information, we design a new document map that leverages a circular grid layout to display documents based on both their relevance to the query and the semantic similarity. Additionally, to improve the interpretability, we introduce a corpus-level attention visualization method to improve the user's understanding of the model focus and to enable the users to identify potential oversight. This visualization, in turn, empowers users to refine, update and introduce new queries, thereby facilitating a dynamic and iterative information-seeking experience. We evaluated VADIS quantitatively and qualitatively on a real-world dataset of biomedical research papers to demonstrate its effectiveness.

关键词： Attention visualization dynamic document representation document visualization biomedical information seeking

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visualization of document Retrieval using External Cluster Relationship

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2013年第1期29卷 35-48页

作者： Jee, Taechang Lee, Hyunjin Lee, Yillbyung Yonsei Univ Sch Comp Sci Seoul 120749 South Korea Korea Soongsil Cyber Univ Dept Comp Informat & Commun Seoul 110340 South Korea

Owing to the limitations of existing visualization schemes, existing document retrieval systems display limited results, often showing only document titles, short summaries, and keywords. This makes it difficult to examine multiple results at once or to find a meaningful relationship between results. This study proposes a new method for the real-time visualization of document retrieval results via clustering. The method clusters similar documents into groups, making it easier to understand the relationship between the retrieved documents. This study also proposes a two-level visualization algorithm which projects the cluster centers onto a two-dimensional space using multidimensional scaling in order to illustrate the relationships among different clusters, and displays individual documents at locations determined by the external cluster relationship in low dimensional space in order to allow the comparison of individual documents. The method was tested on benchmark data and real-world data, and the results show that it is possible to visualize the search results in real time.

关键词： clustering information visualization on-line computation text mining document visualization

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document Cards: A Top Trumps visualization for documents

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2009年第6期15卷 1145-1152页

作者： Strobelt, Hendrik Oelke, Daniela Rohrdantz, Christian Stoffel, Andreas Keim, Daniel A. Deussen, Oliver Univ Konstanz D-7750 Constance Germany

Finding suitable, less space consuming views for a document's main content is crucial to provide convenient access to large document collections on display devices of different size. We present a novel compact visualization which represents the document's key semantic as a mixture of images and important key terms, similar to cards in a top trumps game. The key terms are extracted using an advanced text mining approach based on a fully automatic document structure extraction. The images and their captions are extracted using a graphical heuristic and the captions are used for a semi-semantic image weighting. Furthermore, we use the image color histogram for classification and show at least one representative from each non-empty image class. The approach is demonstrated for the IEEE InfoVis publications of a complete year. The method can easily be applied to other publication collections and sets of documents which contain images.

关键词： document visualization visual summary content extraction document collection browsing

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Information visualization and retrieval using stereoscopic display of document and term relations

Information visualization and retrieval using stereoscopic d...

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Conference on Stereoscopic Displays and Virtual Reality Systems V

作者： Fowler, RH Fowler, WAL Univ Texas Pan Amer Dept Comp Sci Edinburg TX 78539 USA

ISBN: (纸本)0819427357

Scientific visualization brings human perceptual processes to bear in organizing and understanding data about physical phenomena. Information visualization has a similar goal for elements in often semantic domains. document Explorer is an information visualization and retrieval system that displays three dimensional associative network representations of document and term relations. The system's networks of documents can be constructed from existing measures of association, e.g., link structure in hypertexts, or derived by the system using content similarity among documents. The system also maintains a network of terms which is available to the user for query formulation. Recently, we have added stereoscopic display of the system's several networks to enhance users' perception of structure. Additionally, users' head movements are tracked and used to change point and angle of view to further enhance structure perception and allow additional user interface mechanisms for navigation in three dimensions. By viewing and interacting with these networks using head-tracked stereoscopic display the user is better able to perceive relationships in the networks and, thus, better able to distinguish clusters of documents and categories of terms during the information retrieval process.

关键词： information visualization interaction stereoscopic display information retrieval document retrieval document visualization human computer interaction

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document Cards: A Top Trumps visualization for documents

Document Cards: A Top Trumps Visualization for Documents

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IEEE Information visualization Conference/IEEE visualization Conference

作者： Strobelt, Hendrik Oelke, Daniela Rohrdantz, Christian Stoffel, Andreas Keim, Daniel A. Deussen, Oliver Univ Konstanz D-7750 Constance Germany

关键词： document visualization visual summary content extraction document collection browsing

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Normalized compression distance for visual analysis of document collections

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COMPUTERS & GRAPHICS-UK 2007年第3期31卷 327-337页

作者： Telles, G. P. Minghim, R. Paulovich, F. V. Univ Sao Paulo Inst Ciencias Matemat & Comp BR-13560970 Sao Paulo Brazil

In a world flooded by text of various sources, it is of strategic importance to find ways to map information present in written documents in a form that helps users locate and associate important information within a particular text data set. Content-based maps can support extremely useful explorations of text data sets. This paper proposes and evaluates the use of Kolmogorov complexity approximations as a means to detect similarity between general textual documents, in order to support mapping and visualization techniques for corpora exploration. The calculation of this similarity measure requires no intermediate representation of a corpus (such as vector representation) and therefore no pre-processing or parametrization steps. That makes it very attractive for a wider range of exploratory applications compared to conventional measures that need vector-based text representations. The visual layout used here is based on fast distance multi-dimensional projections. It is shown that the similarity measure and the resulting maps present very good precision and that the approach can be used successfully for visual analysis of automatically generated text maps. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： Kolmogorov complexity normalized compression distance text collection visualization multi-dimensional projection document visualization

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