Search (32 results, page 1 of 2)

0.083006896 = product of:
  0.16601379 = sum of:
    0.16601379 = product of:
      0.33202758 = sum of:
        0.33202758 = weight(_text_:tree in 3886) [ClassicSimilarity], result of:
          0.33202758 = score(doc=3886,freq=8.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            1.0139594 = fieldWeight in 3886, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3886)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

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.

0.07621066 = product of:
  0.15242133 = sum of:
    0.15242133 = sum of:
      0.11858127 = weight(_text_:tree in 4573) [ClassicSimilarity], result of:
        0.11858127 = score(doc=4573,freq=2.0), product of:
          0.32745647 = queryWeight, product of:
            6.5552235 = idf(docFreq=170, maxDocs=44218)
            0.049953517 = queryNorm
          0.36212835 = fieldWeight in 4573, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            6.5552235 = idf(docFreq=170, maxDocs=44218)
            0.0390625 = fieldNorm(doc=4573)
      0.03384006 = weight(_text_:22 in 4573) [ClassicSimilarity], result of:
        0.03384006 = score(doc=4573,freq=2.0), product of:
          0.17492871 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.049953517 = queryNorm
          0.19345059 = fieldWeight in 4573, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=4573)
  0.5 = coord(1/2)

Abstract

This study explores how user subject knowledge influences search task processes and outcomes, as well as how search behavior is influenced by subject-oriented information visualization (IV) tools. To enable integrated searches, the proposed WikiMap + integrates search functions and IV tools (i.e., a topic network and hierarchical topic tree) and gathers information from Wikipedia pages and Google Search results. To evaluate the effectiveness of the proposed interfaces, we design subject-oriented tasks and adopt extended evaluation measures. We recruited 48 novices and 48 knowledgeable users, that is, intermediates, for the evaluation. Our results show that novices using the proposed interface demonstrate better search performance than intermediates using Wikipedia. We therefore conclude that our tools help close the gap between novices and intermediates in information searches. The results also show that intermediates can take advantage of the search tool by leveraging the IV tools to browse subtopics, and formulate better queries with less effort. We conclude that embedding the IV and the search tools in the interface can result in different search behavior but improved task performance. We provide implications to design search systems to include IV features adapted to user levels of subject knowledge to help them achieve better task performance.

Date

9.12.2018 16:22:25

0.059290636 = product of:
  0.11858127 = sum of:
    0.11858127 = product of:
      0.23716255 = sum of:
        0.23716255 = weight(_text_:tree in 1102) [ClassicSimilarity], result of:
          0.23716255 = score(doc=1102,freq=8.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.7242567 = fieldWeight in 1102, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1102)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Many large digital collections are currently organized by subject; although useful, these information organization structures are large and complex and thus difficult to browse. Current online tools and visualization prototypes show small, localized subsets and do not provide the ability to explore the predominant patterns of the overall subject structure. This study describes subject tree modifications that facilitate browsing for documents by capitalizing on the highly uneven distribution of real-world collections. The approach is demonstrated on two large collections organized by the Library of Congress Subject Headings (LCSH) and Medical Subject Headings (MeSH). Results show that the LCSH subject tree can be reduced to 49% of its initial complexity while maintaining access to 83% of the collection, and the MeSH tree can be reduced to 45% of its initial complexity while maintaining access to 97% of the collection. A simple solution to negate the loss of access is discussed. The visual impact is demonstrated by using traditional outline views and a slider control allowing searchers to change the subject structure dynamically according to their needs. This study has implications for the development of information organization theory and human-information interaction techniques for subject trees.

0.05869474 = product of:
  0.11738948 = sum of:
    0.11738948 = product of:
      0.23477896 = sum of:
        0.23477896 = weight(_text_:tree in 1456) [ClassicSimilarity], result of:
          0.23477896 = score(doc=1456,freq=4.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.7169776 = fieldWeight in 1456, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1456)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Object

Hyperbolic tree

0.0513472 = product of:
  0.1026944 = sum of:
    0.1026944 = product of:
      0.2053888 = sum of:
        0.2053888 = weight(_text_:tree in 3350) [ClassicSimilarity], result of:
          0.2053888 = score(doc=3350,freq=6.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.62722474 = fieldWeight in 3350, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3350)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Since their beginnings, bibliographic information systems have been displaying results in the form of long, textual lists. With the development of new data models and computer technologies, the need for new approaches to present and interact with bibliographic data has slowly been maturing. To investigate how this could be accomplished, a prototype system, FrbrVis1, was designed to present work families within a bibliographic information system using information visualization. This paper reports on two user studies, a controlled and an observational experiment, that have been carried out to assess the Functional Requirements for Bibliographic Records (FRBR)-based against an existing system as well as to test four different hierarchical visual layouts. The results clearly show that FrbrVis offers better performance and user experience compared to the baseline system. The differences between the four hierarchical visualizations (Indented tree, Radial tree, Circlepack, and Sunburst) were, on the other hand, not as pronounced, but the Indented tree and Sunburst design proved to be the most successful, both in performance as well as user perception. The paper therefore not only evaluates the application of a visual presentation of bibliographic work families, but also provides valuable results regarding the performance and user acceptance of individual hierarchical visualization techniques.

0.050309774 = product of:
  0.10061955 = sum of:
    0.10061955 = product of:
      0.2012391 = sum of:
        0.2012391 = weight(_text_:tree in 1457) [ClassicSimilarity], result of:
          0.2012391 = score(doc=1457,freq=4.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.6145522 = fieldWeight in 1457, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.046875 = fieldNorm(doc=1457)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Footnote

Basiert auf einer Diplomarbeit "Visualisierung von Thesaurus-Strukturen unter besonderer Berücksichtigung eines Hyperbolic Tree Views" an der FH Köln, Institut für Informationswissenschaft, Studiengang Informationswirtschaft, 2004.

Object

Hyperbolic tree

0.04743251 = product of:
  0.09486502 = sum of:
    0.09486502 = product of:
      0.18973003 = sum of:
        0.18973003 = weight(_text_:tree in 1797) [ClassicSimilarity], result of:
          0.18973003 = score(doc=1797,freq=8.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.57940537 = fieldWeight in 1797, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.03125 = fieldNorm(doc=1797)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - The authors introduce two semantics-based navigation applications that facilitate information-seeking activities in internal link-based web sites in Wikipedia. These applications aim to help users find concepts within a topic and related articles on a given topic quickly and then gain topical knowledge from internal link-based encyclopedia web sites. The paper aims to discuss these issues. Design/methodology/approach - The WNavis application consists of three information visualization (IV) tools which are a topic network, a hierarchy topic tree and summaries for topics. The WikiMap application consists of a topic network. The goal of the topic network and topic tree tools is to help users to find the major concepts of a topic and identify relationships between these major concepts easily. In addition, in order to locate specific information and enable users to explore and read topic-related articles quickly, the topic tree and summaries for topics tools support users to gain topical knowledge quickly. The authors then apply the k-clique of cohesive indicator to analyze the sub topics of the seed query and find out the best clustering results via the cosine measure. The authors utilize four metrics, which are correctness, time cost, usage behaviors, and satisfaction, to evaluate the three interfaces. These metrics measure both the outputs and outcomes of applications. As a baseline system for evaluation the authors used a traditional Wikipedia interface. For the evaluation, the authors used an experimental user study with 30 participants.
Findings - The results indicate that both WikiMap and WNavis supported users to identify concepts and their relations better compared to the baseline. In topical tasks WNavis over performed both WikiMap and the baseline system. Although there were no time differences in finding concepts or answering topical questions, the test systems provided users with a greater gain per time unit. The users of WNavis leaned on the hierarchy tree instead of other tools, whereas WikiMap users used the topic map. Research limitations/implications - The findings have implications for the design of IR support tools in knowledge-intensive web sites that help users to explore topics and concepts. Originality/value - The authors explored to what extent the use of each IV support tool contributed to successful exploration of topics in search tasks. The authors propose extended task-based evaluation measures to understand how each application provides useful context for users to accomplish the tasks and attain the search goals. That is, the authors not only evaluate the output of the search results, e.g. the number of relevant items retrieved, but also the outcome provided by the system for assisting users to attain the search goal.

0.045726404 = product of:
  0.09145281 = sum of:
    0.09145281 = sum of:
      0.07114877 = weight(_text_:tree in 3035) [ClassicSimilarity], result of:
        0.07114877 = score(doc=3035,freq=2.0), product of:
          0.32745647 = queryWeight, product of:
            6.5552235 = idf(docFreq=170, maxDocs=44218)
            0.049953517 = queryNorm
          0.21727702 = fieldWeight in 3035, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            6.5552235 = idf(docFreq=170, maxDocs=44218)
            0.0234375 = fieldNorm(doc=3035)
      0.020304035 = weight(_text_:22 in 3035) [ClassicSimilarity], result of:
        0.020304035 = score(doc=3035,freq=2.0), product of:
          0.17492871 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.049953517 = queryNorm
          0.116070345 = fieldWeight in 3035, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0234375 = fieldNorm(doc=3035)
  0.5 = coord(1/2)

Content

As the team describe in a paper posted (http://arxiv.org/abs/1605.04951) on arXiv, they found that figures did indeed matter-but not all in the same way. An average paper in PubMed Central has about one diagram for every three pages and gets 1.67 citations. Papers with more diagrams per page and, to a lesser extent, plots per page tended to be more influential (on average, a paper accrued two more citations for every extra diagram per page, and one more for every extra plot per page). By contrast, including photographs and equations seemed to decrease the chances of a paper being cited by others. That agrees with a study from 2012, whose authors counted (by hand) the number of mathematical expressions in over 600 biology papers and found that each additional equation per page reduced the number of citations a paper received by 22%. This does not mean that researchers should rush to include more diagrams in their next paper. Dr Howe has not shown what is behind the effect, which may merely be one of correlation, rather than causation. It could, for example, be that papers with lots of diagrams tend to be those that illustrate new concepts, and thus start a whole new field of inquiry. Such papers will certainly be cited a lot. On the other hand, the presence of equations really might reduce citations. Biologists (as are most of those who write and read the papers in PubMed Central) are notoriously mathsaverse. If that is the case, looking in a physics archive would probably produce a different result.
Dr Howe and his colleagues do, however, believe that the study of diagrams can result in new insights. A figure showing new metabolic pathways in a cell, for example, may summarise hundreds of experiments. Since illustrations can convey important scientific concepts in this way, they think that browsing through related figures from different papers may help researchers come up with new theories. As Dr Howe puts it, "the unit of scientific currency is closer to the figure than to the paper." With this thought in mind, the team have created a website (viziometrics.org (http://viziometrics.org/) ) where the millions of images sorted by their program can be searched using key words. Their next plan is to extract the information from particular types of scientific figure, to create comprehensive "super" figures: a giant network of all the known chemical processes in a cell for example, or the best-available tree of life. At just one such superfigure per paper, though, the citation records of articles containing such all-embracing diagrams may very well undermine the correlation that prompted their creation in the first place. Call it the ultimate marriage of chart and science.

0.035574384 = product of:
  0.07114877 = sum of:
    0.07114877 = product of:
      0.14229754 = sum of:
        0.14229754 = weight(_text_:tree in 1293) [ClassicSimilarity], result of:
          0.14229754 = score(doc=1293,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.43455404 = fieldWeight in 1293, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.046875 = fieldNorm(doc=1293)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Object

Hyperbolic tree

0.035574384 = product of:
  0.07114877 = sum of:
    0.07114877 = product of:
      0.14229754 = sum of:
        0.14229754 = weight(_text_:tree in 2503) [ClassicSimilarity], result of:
          0.14229754 = score(doc=2503,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.43455404 = fieldWeight in 2503, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.046875 = fieldNorm(doc=2503)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Content

The aim of this study is to develop a software tool, VisuaLCSH, for effective searching, browsing, and maintenance of LCSH. This tool enables visualizing subject headings and hierarchical structures implied and embedded in LCSH. A conceptual framework for converting the hierarchical structure of headings in LCSH to an explicit tree structure is proposed, described, and implemented. The highlights of VisuaLCSH are summarized below: 1) revealing multiple aspects of a heading; 2) normalizing the hierarchical relationships in LCSH; 3) showing multi-level hierarchies in LCSH sub-trees; 4) improving the navigational function of LCSH in retrieval; and 5) enabling the implementation of generic search, i.e., the 'exploding' feature, in searching LCSH.

0.029645318 = product of:
  0.059290636 = sum of:
    0.059290636 = product of:
      0.11858127 = sum of:
        0.11858127 = weight(_text_:tree in 3124) [ClassicSimilarity], result of:
          0.11858127 = score(doc=3124,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.36212835 = fieldWeight in 3124, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3124)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Automated methods for the analysis, modeling, and visualization of large-scale scientometric data provide measures that enable the depiction of the state of world scientific development. We aimed to integrate minimum span clustering (MSC) and minimum spanning tree methods to cluster and visualize the global pattern of scientific publications (PSP) by analyzing aggregated Science Citation Index (SCI) data from 1994 to 2011. We hypothesized that PSP clustering is mainly affected by countries' geographic location, ethnicity, and level of economic development, as indicated in previous studies. Our results showed that the 100 countries with the highest rates of publications were decomposed into 12 PSP groups and that countries within a group tended to be geographically proximal, ethnically similar, or comparable in terms of economic status. Hubs and bridging nodes in each knowledge production group were identified. The performance of each group was evaluated across 16 knowledge domains based on their specialization, volume of publications, and relative impact. Awareness of the strengths and weaknesses of each group in various knowledge domains may have useful applications for examining scientific policies, adjusting the allocation of resources, and promoting international collaboration for future developments.

0.029645318 = product of:
  0.059290636 = sum of:
    0.059290636 = product of:
      0.11858127 = sum of:
        0.11858127 = weight(_text_:tree in 3870) [ClassicSimilarity], result of:
          0.11858127 = score(doc=3870,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.36212835 = fieldWeight in 3870, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3870)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Data from multiple knowledge organization systems are combined to provide a global overview of the content holdings of a small personal library. Subject headings and classification data are used to effectively map the combined book and topic space of the library. While harvested and manipulated by hand, the work reveals issues and potential solutions when using automated techniques to produce topic maps of much larger libraries. The small library visualized consists of the thirty-nine, digital, English language books found in the Osama Bin Laden (OBL) compound in Abbottabad, Pakistan upon his death. As this list of books has garnered considerable media attention, it is worth providing a visual overview of the subject content of these books - some of which is not readily apparent from the titles. Metadata from subject headings and classification numbers was combined to create book-subject maps. Tree maps of the classification data were also produced. The books contain 328 subject headings. In order to enhance the base map with meaningful thematic overlay, library holding count data was also harvested (and aggregated from duplicates). This additional data revealed the relative scarcity or popularity of individual books.

0.023716254 = product of:
  0.04743251 = sum of:
    0.04743251 = product of:
      0.09486502 = sum of:
        0.09486502 = weight(_text_:tree in 4746) [ClassicSimilarity], result of:
          0.09486502 = score(doc=4746,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.28970268 = fieldWeight in 4746, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.03125 = fieldNorm(doc=4746)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

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.

0.023716254 = product of:
  0.04743251 = sum of:
    0.04743251 = product of:
      0.09486502 = sum of:
        0.09486502 = weight(_text_:tree in 5215) [ClassicSimilarity], result of:
          0.09486502 = score(doc=5215,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.28970268 = fieldWeight in 5215, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.03125 = fieldNorm(doc=5215)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The reader of a hypertext document in a web environment, if maximum use of the document is to be obtained, must visualize the overall structure of the paths through the document as well as the document space. Graphic visualization displays of this space, produced to assist in navigation, are classified into four groups, and Heo and Hirtle compare three of these classes as to their effectiveness. Distortion displays expand regions of interest while relatively diminishing the detail of the remaining regions. This technique will show both local detail and global structure. Zoom techniques use a series of increasingly focused displays of smaller and smaller areas, and can reduce cogitative overload, but do not provide an easy movement to other parts of the total space. Expanding outline displays use a tree structure to allow movement through a hierarchy of documents, but if the organization has a wide horizontal structure, or is not particularly hierarchical in nature such display can break down. Three dimensional layouts, which are not evaluated here, place objects by location in three space, providing more information and freedom. However, the space must be represented in two dimensions resulting in difficulty in visually judging depth, size and positioning. Ten students were assigned to each of eight groups composed of viewers of the three techniques and an unassisted control group using either a large (583 selected pages) or a small (50 selected pages) web space. Sets of 10 questions, which were designed to elicit the use of a visualization tool, were provided for each space. Accuracy and time spent were extracted from a log file. Users views were also surveyed after completion. ANOVA shows significant differences in accuracy and time based upon the visualization tool in use. A Tukey test shows zoom accuracy to be significantly less than expanding outline and zoom time to be significantly greater than both the outline and control groups. Size significantly affected accuracy and time, but had no interaction with tool type. While the expanding tool class out performed zoom and distortion, its performance was not significantly different from the control group.

0.020751724 = product of:
  0.041503448 = sum of:
    0.041503448 = product of:
      0.083006896 = sum of:
        0.083006896 = weight(_text_:tree in 4276) [ClassicSimilarity], result of:
          0.083006896 = score(doc=4276,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.25348985 = fieldWeight in 4276, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.02734375 = fieldNorm(doc=4276)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

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.

0.020751724 = product of:
  0.041503448 = sum of:
    0.041503448 = product of:
      0.083006896 = sum of:
        0.083006896 = weight(_text_:tree in 4286) [ClassicSimilarity], result of:
          0.083006896 = score(doc=4286,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.25348985 = fieldWeight in 4286, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.02734375 = fieldNorm(doc=4286)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This chapter reviews visualization techniques that can be used to map the ever-growing domain structure of scientific disciplines and to support information retrieval and classification. In contrast to the comprehensive surveys conducted in traditional fashion by Howard White and Katherine McCain (1997, 1998), this survey not only reviews emerging techniques in interactive data analysis and information visualization, but also depicts the bibliographical structure of the field itself. The chapter starts by reviewing the history of knowledge domain visualization. We then present a general process flow for the visualization of knowledge domains and explain commonly used techniques. In order to visualize the domain reviewed by this chapter, we introduce a bibliographic data set of considerable size, which includes articles from the citation analysis, bibliometrics, semantics, and visualization literatures. Using tutorial style, we then apply various algorithms to demonstrate the visualization effectsl produced by different approaches and compare the results. The domain visualizations reveal the relationships within and between the four fields that together constitute the focus of this chapter. We conclude with a general discussion of research possibilities. Painting a "big picture" of scientific knowledge has long been desirable for a variety of reasons. Traditional approaches are brute forcescholars must sort through mountains of literature to perceive the outlines of their field. Obviously, this is time-consuming, difficult to replicate, and entails subjective judgments. The task is enormously complex. Sifting through recently published documents to find those that will later be recognized as important is labor intensive. Traditional approaches struggle to keep up with the pace of information growth. In multidisciplinary fields of study it is especially difficult to maintain an overview of literature dynamics. Painting the big picture of an everevolving scientific discipline is akin to the situation described in the widely known Indian legend about the blind men and the elephant. As the story goes, six blind men were trying to find out what an elephant looked like. They touched different parts of the elephant and quickly jumped to their conclusions. The one touching the body said it must be like a wall; the one touching the tail said it was like a snake; the one touching the legs said it was like a tree trunk, and so forth. But science does not stand still; the steady stream of new scientific literature creates a continuously changing structure. The resulting disappearance, fusion, and emergence of research areas add another twist to the tale-it is as if the elephant is running and dynamically changing its shape. Domain visualization, an emerging field of study, is in a similar situation. Relevant literature is spread across disciplines that have traditionally had few connections. Researchers examining the domain from a particular discipline cannot possibly have an adequate understanding of the whole. As noted by White and McCain (1997), the new generation of information scientists is technically driven in its efforts to visualize scientific disciplines. However, limited progress has been made in terms of connecting pioneers' theories and practices with the potentialities of today's enabling technologies. If the difference between past and present generations lies in the power of available technologies, what they have in common is the ultimate goal-to reveal the development of scientific knowledge.

0.017787192 = product of:
  0.035574384 = sum of:
    0.035574384 = product of:
      0.07114877 = sum of:
        0.07114877 = weight(_text_:tree in 1202) [ClassicSimilarity], result of:
          0.07114877 = score(doc=1202,freq=2.0), product of:
            0.32745647 = queryWeight, product of:
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.049953517 = queryNorm
            0.21727702 = fieldWeight in 1202, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.5552235 = idf(docFreq=170, maxDocs=44218)
              0.0234375 = fieldNorm(doc=1202)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The concept of c-space is proposed as a visualization schema relating containers of content to cataloging surrogates and classification structures. Possible applications of keyword vector clusters within c-space could include improved retrieval rates through the use of captioning within visual hierarchies, tracings of semantic bleeding among subclasses, and access to buried knowledge within subject-neutral publication containers. The Scholastica Project is described as one example, following a tradition of research dating back to the 1980's. Preliminary focus group assessment indicates that this type of classification rendering may offer digital library searchers enriched entry strategies and an expanded range of re-entry vocabularies. Those of us who work in traditional libraries typically assume that our systems of classification: Library of Congress Classification (LCC) and Dewey Decimal Classification (DDC), are descriptive rather than prescriptive. In other words, LCC classes and subclasses approximate natural groupings of texts that reflect an underlying order of knowledge, rather than arbitrary categories prescribed by librarians to facilitate efficient shelving. Philosophical support for this assumption has traditionally been found in a number of places, from the archetypal tree of knowledge, to Aristotelian categories, to the concept of discursive formations proposed by Michel Foucault. Gary P. Radford has elegantly described an encounter with Foucault's discursive formations in the traditional library setting: "Just by looking at the titles on the spines, you can see how the books cluster together...You can identify those books that seem to form the heart of the discursive formation and those books that reside on the margins. Moving along the shelves, you see those books that tend to bleed over into other classifications and that straddle multiple discursive formations. You can physically and sensually experience...those points that feel like state borders or national boundaries, those points where one subject ends and another begins, or those magical places where one subject has morphed into another..."

0.01692003 = product of:
  0.03384006 = sum of:
    0.03384006 = product of:
      0.06768012 = sum of:
        0.06768012 = weight(_text_:22 in 3406) [ClassicSimilarity], result of:
          0.06768012 = score(doc=3406,freq=2.0), product of:
            0.17492871 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.049953517 = queryNorm
            0.38690117 = fieldWeight in 3406, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.078125 = fieldNorm(doc=3406)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

30. 5.2010 16:22:35

0.01692003 = product of:
  0.03384006 = sum of:
    0.03384006 = product of:
      0.06768012 = sum of:
        0.06768012 = weight(_text_:22 in 2755) [ClassicSimilarity], result of:
          0.06768012 = score(doc=2755,freq=2.0), product of:
            0.17492871 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.049953517 = queryNorm
            0.38690117 = fieldWeight in 2755, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.078125 = fieldNorm(doc=2755)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

1. 2.2016 18:25:22

0.014357123 = product of:
  0.028714245 = sum of:
    0.028714245 = product of:
      0.05742849 = sum of:
        0.05742849 = weight(_text_:22 in 3355) [ClassicSimilarity], result of:
          0.05742849 = score(doc=3355,freq=4.0), product of:
            0.17492871 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.049953517 = queryNorm
            0.32829654 = fieldWeight in 3355, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=3355)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

22. 1.2017 16:54:03
22. 1.2017 17:10:56