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Platis, N. et al.: Visualization of uncertainty in tag clouds (2016)
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- Date
- 1. 2.2016 18:25:22
- Language
- e
- Source
- Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
-
Lindstrom, N.; Malmsten, M.: Building interfaces on a networked graph (2015)
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- Language
- e
- Source
- Linked data and user interaction: the road ahead. Eds.: Cervone, H.F. u. L.G. Svensson
-
Yukimo Kobashio, N.; Santos, R.N.M.: Information organization and representation by graphic devices : an interdisciplinary approach (2007)
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- Language
- e
- Source
- ¬La interdisciplinariedad y la transdisciplinariedad en la organización del conocimiento científico : actas del VIII Congreso ISKO-España, León, 18, 19 y 20 de Abril de 2007 : Interdisciplinarity and transdisciplinarity in the organization of scientific knowledge. Ed.: B. Rodriguez Bravo u. M.L Alvite Diez
-
Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Large, A.; Beheshti, J.; Tabatabaei, N.; Nesset, V.: Developing a visual taxonomy : children's views on aesthetics (2009)
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-
Zhu, B.; Chen, H.: Information visualization (2004)
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- Abstract
- Advanced technology has resulted in the generation of about one million terabytes of information every year. Ninety-reine percent of this is available in digital format (Keim, 2001). More information will be generated in the next three years than was created during all of previous human history (Keim, 2001). Collecting information is no longer a problem, but extracting value from information collections has become progressively more difficult. Various search engines have been developed to make it easier to locate information of interest, but these work well only for a person who has a specific goal and who understands what and how information is stored. This usually is not the Gase. Visualization was commonly thought of in terms of representing human mental processes (MacEachren, 1991; Miller, 1984). The concept is now associated with the amplification of these mental processes (Card, Mackinlay, & Shneiderman, 1999). Human eyes can process visual cues rapidly, whereas advanced information analysis techniques transform the computer into a powerful means of managing digitized information. Visualization offers a link between these two potent systems, the human eye and the computer (Gershon, Eick, & Card, 1998), helping to identify patterns and to extract insights from large amounts of information. The identification of patterns is important because it may lead to a scientific discovery, an interpretation of clues to solve a crime, the prediction of catastrophic weather, a successful financial investment, or a better understanding of human behavior in a computermediated environment. Visualization technology shows considerable promise for increasing the value of large-scale collections of information, as evidenced by several commercial applications of TreeMap (e.g., http://www.smartmoney.com) and Hyperbolic tree (e.g., http://www.inxight.com) to visualize large-scale hierarchical structures. Although the proliferation of visualization technologies dates from the 1990s where sophisticated hardware and software made increasingly faster generation of graphical objects possible, the role of visual aids in facilitating the construction of mental images has a long history. Visualization has been used to communicate ideas, to monitor trends implicit in data, and to explore large volumes of data for hypothesis generation. Imagine traveling to a strange place without a map, having to memorize physical and chemical properties of an element without Mendeleyev's periodic table, trying to understand the stock market without statistical diagrams, or browsing a collection of documents without interactive visual aids. A collection of information can lose its value simply because of the effort required for exhaustive exploration. Such frustrations can be overcome by visualization.
Visualization can be classified as scientific visualization, software visualization, or information visualization. Although the data differ, the underlying techniques have much in common. They use the same elements (visual cues) and follow the same rules of combining visual cues to deliver patterns. They all involve understanding human perception (Encarnacao, Foley, Bryson, & Feiner, 1994) and require domain knowledge (Tufte, 1990). Because most decisions are based an unstructured information, such as text documents, Web pages, or e-mail messages, this chapter focuses an the visualization of unstructured textual documents. The chapter reviews information visualization techniques developed over the last decade and examines how they have been applied in different domains. The first section provides the background by describing visualization history and giving overviews of scientific, software, and information visualization as well as the perceptual aspects of visualization. The next section assesses important visualization techniques that convert abstract information into visual objects and facilitate navigation through displays an a computer screen. It also explores information analysis algorithms that can be applied to identify or extract salient visualizable structures from collections of information. Information visualization systems that integrate different types of technologies to address problems in different domains are then surveyed; and we move an to a survey and critique of visualization system evaluation studies. The chapter concludes with a summary and identification of future research directions.
- Language
- e
-
Nehmadi, L.; Meyer, J.; Parmet, Y.; Ben-Asher, N.: Predicting a screen area's perceived importance from spatial and physical attributes (2011)
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- Language
- e
-
Thissen, F.: Screen-Design-Handbuch : Effektiv informieren und kommunizieren mit Multimedia (2001)
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- Classification
- JZN (E)
- Date
- 22. 3.2008 14:35:21
- GHBS
- JZN (E)
- Issue
- 2., überarb. u. erw. Aufl.
-
Wilson, M.: Interfaces for information retrieval (2011)
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- Language
- e
- Source
- Interactive information seeking, behaviour and retrieval. Eds.: Ruthven, I. u. D. Kelly
-
Quirin, A.; Cordón, O.; Santamaría, J.; Vargas-Quesada, B.; Moya-Anegón, F.: ¬A new variant of the Pathfinder algorithm to generate large visual science maps in cubic time (2008)
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- Abstract
- In the last few years, there is an increasing interest to generate visual representations of very large scientific domains. A methodology based on the combined use of ISI-JCR category cocitation and social networks analysis through the use of the Pathfinder algorithm has demonstrated its ability to achieve high quality, schematic visualizations for these kinds of domains. Now, the next step would be to generate these scientograms in an on-line fashion. To do so, there is a need to significantly decrease the run time of the latter pruning technique when working with category cocitation matrices of a large dimension like the ones handled in these large domains (Pathfinder has a time complexity order of O(n4), with n being the number of categories in the cocitation matrix, i.e., the number of nodes in the network). Although a previous improvement called Binary Pathfinder has already been proposed to speed up the original algorithm, its significant time complexity reduction is not enough for that aim. In this paper, we make use of a different shortest path computation from classical approaches in computer science graph theory to propose a new variant of the Pathfinder algorithm which allows us to reduce its time complexity in one order of magnitude, O(n3), and thus to significantly decrease the run time of the implementation when applied to large scientific domains considering the parameter q = n - 1. Besides, the new algorithm has a much simpler structure than the Binary Pathfinder as well as it saves a significant amount of memory with respect to the original Pathfinder by reducing the space complexity to the need of just storing two matrices. An experimental comparison will be developed using large networks from real-world domains to show the good performance of the new proposal.
- Language
- e
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Pejtersen, A.M.: Implications of users' value perception for the design of a bibliographic retrieval system (1986)
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- Language
- e
- Source
- Empirical foundation of information and software science. Ed.: J.C. Agarwal u. P. Zunde
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Di Maio, P.: Linked data beyond libraries : towards universal interfaces and knowledge unification (2015)
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- Language
- e
- Source
- Linked data and user interaction: the road ahead. Eds.: Cervone, H.F. u. L.G. Svensson
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Maaten, L. van den: Accelerating t-SNE using Tree-Based Algorithms (2014)
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- Abstract
- The paper investigates the acceleration of t-SNE-an embedding technique that is commonly used for the visualization of high-dimensional data in scatter plots-using two tree-based algorithms. In particular, the paper develops variants of the Barnes-Hut algorithm and of the dual-tree algorithm that approximate the gradient used for learning t-SNE embeddings in O(N*logN). Our experiments show that the resulting algorithms substantially accelerate t-SNE, and that they make it possible to learn embeddings of data sets with millions of objects. Somewhat counterintuitively, the Barnes-Hut variant of t-SNE appears to outperform the dual-tree variant.
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Aletras, N.; Baldwin, T.; Lau, J.H.; Stevenson, M.: Evaluating topic representations for exploring document collections (2017)
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- Abstract
- Topic models have been shown to be a useful way of representing the content of large document collections, for example, via visualization interfaces (topic browsers). These systems enable users to explore collections by way of latent topics. A standard way to represent a topic is using a term list; that is the top-n words with highest conditional probability within the topic. Other topic representations such as textual and image labels also have been proposed. However, there has been no comparison of these alternative representations. In this article, we compare 3 different topic representations in a document retrieval task. Participants were asked to retrieve relevant documents based on predefined queries within a fixed time limit, presenting topics in one of the following modalities: (a) lists of terms, (b) textual phrase labels, and (c) image labels. Results show that textual labels are easier for users to interpret than are term lists and image labels. Moreover, the precision of retrieved documents for textual and image labels is comparable to the precision achieved by representing topics using term lists, demonstrating that labeling methods are an effective alternative topic representation.
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- e
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Julien, C.-A.; Leide, J.E.; Bouthillier, F.: Controlled user evaluations of information visualization interfaces for text retrieval : literature review and meta-analysis (2008)
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- Abstract
- This review describes experimental designs (users, search tasks, measures, etc.) used by 31 controlled user studies of information visualization (IV) tools for textual information retrieval (IR) and a meta-analysis of the reported statistical effects. Comparable experimental designs allow research designers to compare their results with other reports, and support the development of experimentally verified design guidelines concerning which IV techniques are better suited to which types of IR tasks. The studies generally use a within-subject design with 15 or more undergraduate students performing browsing to known-item tasks on sets of at least 1,000 full-text articles or Web pages on topics of general interest/news. Results of the meta-analysis (N = 8) showed no significant effects of the IV tool as compared with a text-only equivalent, but the set shows great variability suggesting an inadequate basis of comparison. Experimental design recommendations are provided which would support comparison of existing IV tools for IR usability testing.
- Language
- e
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Su, H.-N.: Visualization of global science and technology policy research structure (2012)
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- Language
- e
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Wu, Y.; Bai, R.: ¬An event relationship model for knowledge organization and visualization (2017)
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- Abstract
- An event is a specific occurrence involving participants, which is a typed, n-ary association of entities or other events, each identified as a participant in a specific semantic role in the event (Pyysalo et al. 2012; Linguistic Data Consortium 2005). Event types may vary across domains. Representing relationships between events can facilitate the understanding of knowledge in complex systems (such as economic systems, human body, social systems). In the simplest form, an event can be represented as Entity A <Relation> Entity B. This paper evaluates several knowledge organization and visualization models and tools, such as concept maps (Cmap), topic maps (Ontopia), network analysis models (Gephi), and ontology (Protégé), then proposes an event relationship model that aims to integrate the strengths of these models, and can represent complex knowledge expressed in events and their relationships.
- Language
- e
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Sidhom, S.; Hassoun, M.: Morpho-syntactic parsing to text mining environment : NP recognition model to knowledge visualization and information (2003)
0.02
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- Language
- e
- Source
- Tendencias de investigación en organización del conocimient: IV Cologuio International de Ciencas de la Documentación , VI Congreso del Capitulo Espanol de ISKO = Trends in knowledge organization research. Eds.: J.A. Frias u. C. Travieso
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Kocijan, K.: Visualizing natural language resources (2015)
0.02
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- Language
- e
- Source
- Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
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Ahn, J.-w.; Brusilovsky, P.: Adaptive visualization for exploratory information retrieval (2013)
0.02
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
