Search (47 results, page 1 of 3)

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Source

Information processing and management. 37(2001) no.4, S.639-657

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Abstract

The VIBE (Visual Information Browsing Environment) prototype system, which was developed at Molde College in Norway in conjunction with researchers at the University of Pittsburgh, allows users to evaluate documents from a retrieved set that is graphically represented as geometric icons within one screen display. While the formal modeling behind VIBE and other information visualization retrieval systems is weIl known, user interaction with the system is not. This investigation tested the designer assumption that VIBE is a tool for a smart (expert) user and asked: What are the effects of the different levels of user expertise upon VIBE usability? Three user groups including novices, online searching experts, and VIBE system experts totaling 31 participants were tested over two sessions with VIBE. Participants selected appropriate features to complete tasks, but did not always solve the tasks correctly. Task timings improved over repeated use with VIBE and the nontypical visually oriented tasks were resolved more successfully than others. Statistically significant differences were not found among all parameters examined between novices and online experts. The VIBE system experts provided the predicted baseline for this study and the VIBE designer assumption was shown to be correct. The study's results point toward further exploration of cognitive preattentive processing, which may help to understand better the novice/expert paradigm when testing a visualized interface design for information retrieval.

Source

Journal of the American Society for Information Science and Technology. 56(2005) no.8, S.824-833

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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.

Source

Information processing and management. 44(2008) no.4, S.1611-1623

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Abstract

Purpose - This paper aims to explore the theory and practice of knowledge organization and its necessary connection to human perception, and shows a solution of the potential ones. Design/methodology/approach - The author attempts to survey the problem of concept-building and extension, as well as the determination of semantics in different aspects. The purpose is to find criteria for the choice of the solution that best incorporates users into the design cycles of knowledge organization systems. Findings - It is widely agreed that cognition provides the basis for concept-building; however, at the next stage of processing there is a debate. Fundamentally, what is the connection between perception and the superior cognitive processes? The perceptual method does not separate these two but rather considers them united, with perception permeating cognition. By contrast, the linguistic method considers perception as an information-receiving system. Separate from, and following, perception, the cognitive subsystems then perform information and data processing, leading to both knowledge organization and representation. We assume by that model that top-level concepts emerge from knowledge organization and representation. This paper points obvious connection of visual imagery and the internet; perceptual access of knowledge organization and information retrieval. There are some practical and characteristic solutions for the visualization of information without demand of completeness. Research limitations/implications - Librarians need to identify those semantic characteristics which stimulate a similar conceptual image both in the mind of the librarian and in the mind of the user. Originality/value - For a fresh perspective, an understanding of perception is required as well.

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Content

Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".

Date

20. 1.2008 17:28:29

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Source

Information processing and management. 41(2005) no.4, S.1003-1018

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Date

22. 3.2008 14:29:25

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Source

Information processing and management. 39(2003) no.6, S.923-940

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Abstract

This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.

Date

22. 7.2006 16:11:05

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.359-377

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Abstract

Many real-world domains can be represented as large node-link graphs: backbone Internet routers connect with 70,000 other hosts, mid-sized Web servers handle between 20,000 and 200,000 hyperlinked documents, and dictionaries contain millions of words defined in terms of each other. Computational manipulation of such large graphs is common, but previous tools for graph visualization have been limited to datasets of a few thousand nodes. Visual depictions of graphs and networks are external representations that exploit human visual processing to reduce the cognitive load of many tasks that require understanding of global or local structure. We assert that the two key advantages of computer-based systems for information visualization over traditional paper-based visual exposition are interactivity and scalability. We also argue that designing visualization software by taking the characteristics of a target user's task domain into account leads to systems that are more effective and scale to larger datasets than previous work. This thesis contains a detailed analysis of three specialized systems for the interactive exploration of large graphs, relating the intended tasks to the spatial layout and visual encoding choices. We present two novel algorithms for specialized layout and drawing that use quite different visual metaphors. The H3 system for visualizing the hyperlink structures of web sites scales to datasets of over 100,000 nodes by using a carefully chosen spanning tree as the layout backbone, 3D hyperbolic geometry for a Focus+Context view, and provides a fluid interactive experience through guaranteed frame rate drawing. The Constellation system features a highly specialized 2D layout intended to spatially encode domain-specific information for computational linguists checking the plausibility of a large semantic network created from dictionaries. The Planet Multicast system for displaying the tunnel topology of the Internet's multicast backbone provides a literal 3D geographic layout of arcs on a globe to help MBone maintainers find misconfigured long-distance tunnels. Each of these three systems provides a very different view of the graph structure, and we evaluate their efficacy for the intended task. We generalize these findings in our analysis of the importance of interactivity and specialization for graph visualization systems that are effective and scalable.

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Date

29.12.2007 18:17:29

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Date

30. 5.2010 16:22:35

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Date

23. 3.2008 19:10:22

Footnote

Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.
With contributors almost exclusively from the computer science field, the intended audience of this work is heavily slanted towards a computer science perspective. However, it is highly readable and provides introductory material that would be useful to information scientists from a variety of domains. Yet, much interesting work in information visualization from other fields could have been included giving the work more of an interdisciplinary perspective to complement their goals of integrating work in this area. Unfortunately, many of the application chapters are these, shallow, and lack complementary illustrations of visualization techniques or user interfaces used. However, they do provide insight into the many applications being developed in this rapidly expanding field. The authors have successfully put together a highly useful reference text for the data mining and information visualization communities. Those interested in a good introduction and overview of complementary research areas in these fields will be satisfied with this collection of papers. The focus upon integrating data visualization with data mining complements texts in each of these fields, such as Advances in Knowledge Discovery and Data Mining (Fayyad et al., MIT Press) and Readings in Information Visualization: Using Vision to Think (Card et. al., Morgan Kauffman). This unique work is a good starting point for future interaction between researchers in the fields of data visualization and data mining and makes a good accompaniment for a course focused an integrating these areas or to the main reference texts in these fields."

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Date

29. 1.2005 19:19:29

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Abstract

We propose an approach to visualizing the scientific world and its evolution by constructing minimum spanning trees (MSTs) and a two-dimensional map of scientific journals using the database of the Science Citation Index (SCI) during 1994-2001. The structures of constructed MSTs are consistent with the sorting of SCI categories. The map of science is constructed based on our MST results. Such a map shows the relation among various knowledge clusters and their citation properties. The temporal evolution of the scientific world can also be delineated in the map. In particular, this map clearly shows a linear structure of the scientific world, which contains three major domains including physical sciences, life sciences, and medical sciences. The interaction of various knowledge fields can be clearly seen from this scientific world map. This approach can be applied to various levels of knowledge domains.

Object

Science Citation Index
Map of Science

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.11, S.1461-1469

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Date

25.10.2007 9:51:29

Source

Wa(h)re Information: 29. Österreichischer Bibliothekartag Bregenz, 19.-23.9.2006. Hrsg.: Harald Weigel

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Date

25. 2.2012 13:51:29

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Date

28. 9.2008 19:16:29

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Date

30. 1.2007 18:22:41

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Source

Information - Wissenschaft und Praxis. 56(2005) H.1, S.29-34