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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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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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ParlaMint in TEITOK 4

ParlaMint in TEITOK

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4th Workshop on Creating, Analysing, and Increasing Accessibility of Parliamentary Corpora, ParlaCLARIN 2024

作者： Janssen, Maarten Kopp, Matyáš Charles University Faculty of Mathematics and Physics Prague Czech Republic

ISBN: (纸本)9782493814241

This paper describes the ParlaMint 4.0 parliamentary corpora as made available in TEITOK at LINDAT. The TEITOK interface makes it possible to search through the corpus, to view each session in a readable manner, and to explore the names in the corpus. The interface does not present any new data, but provides an access point to the ParlaMint corpus that is less oriented to linguistic use only, and more accessible for the general public or researchers from other fields. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： document visualization ParlaMint TEITOK

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VIStory: interactive storyboard for exploring visual information in scientific publications

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JOURNAL OF visualization 2021年第1期24卷 69-84页

作者： Zeng, Wei Dong, Ao Chen, Xi Cheng, Zhang-lin Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

Many visual analytics have been developed for examining scientific publications comprising wealthy data such as authors and citations. The studies provide unprecedented insights on a variety of applications, e.g., literature review and collaboration analysis. However, visual information (e.g., figures) that is widely employed for storytelling and methods description are often neglected. We presentVIStory, an interactive storyboard for exploring visual information in scientific publications. We harvest a new dataset of a large corpora of figures, using an automatic figure extraction method. Each figure contains various attributes such as dominant color and width/height ratio, together with faceted metadata of the publication including venues, authors, and keywords. To depict these information, we develop an intuitive interface consisting of three components: (1) Faceted View enables efficient query by publication metadata, benefiting from a nested table structure, (2) Storyboard View arranges paper rings-a well-designed glyph for depicting figure attributes, in a themeriver layout to reveal temporal trends, and (3) Endgame View presents a highlighted figure together with the publication metadata. We illustrate the applicability ofVIStorywith case studies on two datasets, i.e., 10-year IEEE VIS publications, and publications by a research team at CVPR, ICCV, and ECCV conferences. Quantitative and qualitative results from a formal user study demonstrate the efficiency ofVIStoryin exploring visual information in scientific publications.

关键词： document visualization Image browser Faceted metadata

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Visual Quality Guidance for document Exploration with Focus plus Context Techniques

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2020年第8期26卷 2715-2731页

作者： Han, Qi Thom, Dennis John, Markus Koch, Steffen Heimerl, Florian Ertl, Thomas Univ Stuttgart Inst Visualisat & Interact Syst D-70174 Stuttgart Germany Univ Wisconsin Dept Comp Sci 1210 W Dayton St Madison WI 53706 USA

Magic lens based focus+context techniques are powerful means for exploring document spatializations. Typically, they only offer additional summarized or abstracted views on focused documents. As a consequence, users might miss important information that is either not shown in aggregated form or that never happens to get focused. In this work, we present the design process and user study results for improving a magic lens based document exploration approach with exemplary visual quality cues to guide users in steering the exploration and support them in interpreting the summarization results. We contribute a thorough analysis of potential sources of information loss involved in these techniques, which include the visual spatialization of text documents, user-steered exploration, and the visual summarization. With lessons learned from previous research, we highlight the various ways those information losses could hamper the exploration. Furthermore, we formally define measures for the aforementioned different types of information losses and bias. Finally, we present the visual cues to depict these quality measures that are seamlessly integrated into the exploration approach. These visual cues guide users during the exploration and reduce the risk of misinterpretation and accelerate insight generation. We conclude with the results of a controlled user study and discuss the benefits and challenges of integrating quality guidance in exploration techniques.

关键词： visualization Loss measurement Lenses Data visualization Two dimensional displays Uncertainty Text analysis document visualization focus plus context visual guidance uncertainty visualization document spatialization text mining visual analytics

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Modeling How Humans Judge Dot-Label Relations in Point Cloud visualizations

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2020年第6期26卷 2144-2155页

作者： Reckziegel, Martin Pfeiffer, Linda Heine, Christian Janicke, Stefan Univ Leipzig Image & Signal Proc Grp Leipzig Germany Univ Leipzig Leipzig Germany German Aerosp Ctr DLR Visual Analyt Grp Inst Data Sci Cologne Germany Univ Southern Denmark Dept Math & Comp Sci Odense Denmark

When point clouds are labeled in information visualization applications, sophisticated guidelines as in cartography do not yet exist. Existing naive strategies may mislead as to which points belong to which label. To inform improved strategies, we studied factors influencing this phenomenon. We derived a class of labeled point cloud representations from existing applications and we defined different models predicting how humans interpret such complex representations, focusing on their geometric properties. We conducted an empirical study, in which participants had to relate dots to labels in order to evaluate how well our models predict. Our results indicate that presence of point clusters, label size, and angle to the label have an effect on participants' judgment as well as that the distance measure types considered perform differently discouraging the use of label centers as reference points.

关键词： Human judgment model document visualization label placement

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COVID-19 Kaggle Literature Organization 20

COVID-19 Kaggle Literature Organization

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20th ACM Symposium on document Engineering (DocEng)

作者： Eren, Maksim Ekin Solovyev, Nick Raff, Edward Nicholas, Charles Ben Johnson Univ Maryland Baltimore Cty Baltimore MD 21228 USA Booz Allen Hamilton Hamilton ON Canada

ISBN: (纸本)9781450380003

The world has faced the devastating outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), or COVID-19, in 2020. Research in the subject matter was fast-tracked to such a point that scientists were struggling to keep up with new findings. With this increase in the scientific literature, there arose a need for organizing those documents. We describe an approach to organize and visualize the scientific literature on or related to COVID-19 using machine learning techniques so that papers on similar topics are grouped together. By doing so, the navigation of topics and related papers is simplified. We implemented this approach using the widely recognized CORD-19 dataset to present a publicly available proof of concept.

关键词： COVID-19 dimensionality reduction clustering document visualization

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VIS Author Profiles: Interactive Descriptions of Publication Records Combining Text and visualization

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2019年第1期25卷 152-161页

作者： Latif, Shahid Beck, Fabian Univ Duisburg Essen Paluno Duisburg Germany

Publication records and collaboration networks are important for assessing the expertise and experience of researchers. Existing digital libraries show the raw publication lists in author profiles, whereas visualization techniques focus on specific subproblems. Instead, we look at publication records from various perspectives mixing low-level publication data with high-level abstractions and background information. This work presents VIS Author Profiles, a novel approach to generate integrated textual and visual descriptions to highlight patterns in publication records. We leverage template-based natural language generation to summarize notable publication statistics, evolution of research topics, and collaboration relationships. Seamlessly integrated visualizations augment the textual description and are interactively connected with each other and the text. The underlying publication data and detailed explanations of the analysis are available on demand. We compare our approach to existing systems by taking into account information needs of users and demonstrate its usefulness in two realistic application examples.

关键词： Terms Natural language generation document visualization interactive documents sparklines digital libraries

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VIStory: Interactive Storyboard for Exploring Visual Information in Scientific Publications 19

VIStory: Interactive Storyboard for Exploring Visual Informa...

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12th International Symposium on Visual Information Communication and Interaction (VINCI)

作者： Dong, Ao Zeng, Wei Chen, Xi Cheng, Zhanglin Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Univ Chinese Acad Sci Shenzhen Peoples R China Shenzhen Inst Adv Technol Shenzhen Peoples R China Chinese Acad Sci Shenzhen Peoples R China

ISBN: (纸本)9781450376266

Many visual analytics have been developed for examining scientific publications comprising wealthy data such as authors and citations. The studies provide unprecedented insights on a variety of applications, e.g., literature review and collaboration analysis. However, visual information (i.e., figures) that are widely employed for storytelling and methods description are often neglected. We present VIStory, an interactive storyboard for exploring visual information in scientific publications. We harvest the data using an automatic figure extraction method, resulting in a large corpora of figures. Each figure contains various attributes such as dominant color and width/height ratio, together with faceted metadata of the publication including venues, authors, and keywords. To depict these information, we develop an intuitive interface consisting of three components: 1) Faceted View enables efficient query by publication metadata, benefiting from a nested table structure, 2) Storyboard View arranges paper rings a well-designed glyph for depicting figure attributes, in a themeriver layout to reveal temporal trends, and 3) Endgame View presents a highlighted figure together with the publication metadata. The system is especially useful for scientific publications containing substantial visual information, such as the visualization publications. We demonstrate the effectiveness of our approach using two case studies conducted on past ten-year IEEE VIS publications in 2009 - 2018.

关键词： visualization survey document visualization image browser faceted metadata

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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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