Search (24 results, page 1 of 2)

0.15585195 = product of:
  0.2078026 = sum of:
    0.027355144 = weight(_text_:science in 5272) [ClassicSimilarity], result of:
      0.027355144 = score(doc=5272,freq=4.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.20579056 = fieldWeight in 5272, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5272)
    0.06807269 = weight(_text_:research in 5272) [ClassicSimilarity], result of:
      0.06807269 = score(doc=5272,freq=18.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.47281966 = fieldWeight in 5272, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5272)
    0.11237476 = sum of:
      0.078189164 = weight(_text_:network in 5272) [ClassicSimilarity], result of:
        0.078189164 = score(doc=5272,freq=4.0), product of:
          0.22473325 = queryWeight, product of:
            4.4533744 = idf(docFreq=1398, maxDocs=44218)
            0.050463587 = queryNorm
          0.34791988 = fieldWeight in 5272, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            4.4533744 = idf(docFreq=1398, maxDocs=44218)
            0.0390625 = fieldNorm(doc=5272)
      0.034185596 = weight(_text_:22 in 5272) [ClassicSimilarity], result of:
        0.034185596 = score(doc=5272,freq=2.0), product of:
          0.17671488 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.050463587 = queryNorm
          0.19345059 = fieldWeight in 5272, 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=5272)
  0.75 = coord(3/4)

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

0.05221905 = product of:
  0.1044381 = sum of:
    0.046423215 = weight(_text_:science in 4840) [ClassicSimilarity], result of:
      0.046423215 = score(doc=4840,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.34923816 = fieldWeight in 4840, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.09375 = fieldNorm(doc=4840)
    0.058014885 = product of:
      0.11602977 = sum of:
        0.11602977 = weight(_text_:22 in 4840) [ClassicSimilarity], result of:
          0.11602977 = score(doc=4840,freq=4.0), product of:
            0.17671488 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050463587 = queryNorm
            0.6565931 = fieldWeight in 4840, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.09375 = fieldNorm(doc=4840)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Date

22. 2.2003 17:25:39
22. 2.2003 18:13:11

Series

Lecture notes in computer science; 2539

0.05221905 = product of:
  0.1044381 = sum of:
    0.046423215 = weight(_text_:science in 1359) [ClassicSimilarity], result of:
      0.046423215 = score(doc=1359,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.34923816 = fieldWeight in 1359, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.09375 = fieldNorm(doc=1359)
    0.058014885 = product of:
      0.11602977 = sum of:
        0.11602977 = weight(_text_:22 in 1359) [ClassicSimilarity], result of:
          0.11602977 = score(doc=1359,freq=4.0), product of:
            0.17671488 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050463587 = queryNorm
            0.6565931 = fieldWeight in 1359, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.09375 = fieldNorm(doc=1359)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Date

22. 2.2003 17:25:39
22. 2.2003 18:20:07

Series

Lecture notes in computer science; 2539

0.04434503 = product of:
  0.059126705 = sum of:
    0.019343007 = weight(_text_:science in 671) [ClassicSimilarity], result of:
      0.019343007 = score(doc=671,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.1455159 = fieldWeight in 671, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0390625 = fieldNorm(doc=671)
    0.0226909 = weight(_text_:research in 671) [ClassicSimilarity], result of:
      0.0226909 = score(doc=671,freq=2.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.15760657 = fieldWeight in 671, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.0390625 = fieldNorm(doc=671)
    0.017092798 = product of:
      0.034185596 = sum of:
        0.034185596 = weight(_text_:22 in 671) [ClassicSimilarity], result of:
          0.034185596 = score(doc=671,freq=2.0), product of:
            0.17671488 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050463587 = queryNorm
            0.19345059 = fieldWeight in 671, 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=671)
      0.5 = coord(1/2)
  0.75 = coord(3/4)

Abstract

Although it is commonly expected that the citation context of a reference is likely to provide more detailed and direct information about the nature of a citation, few studies in the literature have specifically addressed the extent to which the information in different parts of a scientific publication differs. Do abstracts tend to use conceptually broader terms than sentences in a citation context in the body of a publication? In this article, we propose a method to analyze and compare latent topics in scientific publications, in particular, from abstracts of papers that cited a target reference and from sentences that cited the target reference. We conducted an experiment and applied topical modeling techniques to full-text papers in eight biomedicine journals. Topics derived from the two sources are compared in terms of their similarities and broad-narrow relationships defined based on information entropy. The results show that abstracts and citation contexts are characterized by distinct sets of topics with moderate overlaps. Furthermore, the results confirm that topics from abstracts of citing papers have broader terms than topics from citation contexts formed by citing sentences. The method and the findings could be used to enhance and extend the current methodologies for research evaluation and citation evaluation.

Date

22. 3.2013 19:50:00

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.627-639

0.03506255 = product of:
  0.0701251 = sum of:
    0.023211608 = weight(_text_:science in 602) [ClassicSimilarity], result of:
      0.023211608 = score(doc=602,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.17461908 = fieldWeight in 602, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.046875 = fieldNorm(doc=602)
    0.046913497 = product of:
      0.093826994 = sum of:
        0.093826994 = weight(_text_:network in 602) [ClassicSimilarity], result of:
          0.093826994 = score(doc=602,freq=4.0), product of:
            0.22473325 = queryWeight, product of:
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.050463587 = queryNorm
            0.41750383 = fieldWeight in 602, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.046875 = fieldNorm(doc=602)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

In this article we demonstrate the use of an integrative approach to visualizing and tracking the development of scientific paradigms. This approach is designed to reveal the long-term process of competing scientific paradigms. We assume that a cluster of highly cited and cocited scientific publications in a cocitation network represents the core of a predominant scientific paradigm. The growth of a paradigm is depicted and animated through the rise of citation rates and the movement of its core cluster towards the center of the cocitation network. We study two cases of competing scientific paradigms in the real world: (1) the causes of mass extinctions, and (2) the connections between mad cow disease and a new variant of a brain disease in humans-vCJD. Various theoretical and practical issues concerning this approach are discussed.

Source

Journal of the American Society for Information Science and technology. 53(2002) no.8, S.678.689

0.033543546 = product of:
  0.06708709 = sum of:
    0.04893437 = weight(_text_:science in 2213) [ClassicSimilarity], result of:
      0.04893437 = score(doc=2213,freq=20.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.36812937 = fieldWeight in 2213, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.03125 = fieldNorm(doc=2213)
    0.01815272 = weight(_text_:research in 2213) [ClassicSimilarity], result of:
      0.01815272 = score(doc=2213,freq=2.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.12608525 = fieldWeight in 2213, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.03125 = fieldNorm(doc=2213)
  0.5 = coord(2/4)

Footnote

Rez. in: JASIST 55(2004) no.4, S.363-365 (J.W. Schneider): "Theories and methods for mapping scientific frontiers have existed for decades-especially within quantitative studies of science. This book investigates mapping scientific frontiers from the perspective of visual thinking and visual exploration (visual communication). The central theme is construction of visual-spatial representations that may convey insights into the dynamic structure of scientific frontiers. The author's previous book, Information Visualisation and Virtual Environments (1999), also concerns some of the ideas behind and possible benefits of visual communication. This new book takes a special focus an knowledge visualization, particularly in relation to science literature. The book is not a technical tutorial as the focus is an principles of visual communication and ways that may reveal the dynamics of scientific frontiers. The new approach to science mapping presented is the culmination of different approaches from several disciplines, such as philosophy of science, information retrieval, scientometrics, domain analysis, and information visualization. The book therefore addresses an audience with different disciplinary backgrounds and tries to stimulate interdisciplinary research. Chapter 1, The Growth of Scientific Knowledge, introduces a range of examples that illustrate fundamental issues concerning visual communication in general and science mapping in particular. Chapter 2, Mapping the Universe, focuses an the basic principles of cartography for visual communication. Chapter 3, Mapping the Mind, turns the attention inward and explores the design of mind maps, maps that represent our thoughts, experience, and knowledge. Chapter 4, Enabling Techniques for Science Mapping, essentially outlines the author's basic approach to science mapping.
The title of Chapter 5, On the Shoulders of Giants, implies that knowledge of the structure of scientific frontiers in the immediate past holds the key to a fruitful exploration of people's intellectual assets. Chapter 6, Tracing Competing Paradigms explains how information visualization can draw upon the philosophical framework of paradigm shifts and thereby enable scientists to track the development of Competing paradigms. The final chapter, Tracking Latent Domain Knowledge, turns citation analysis upside down by looking at techniques that may reveal latent domain knowledge. Mapping Scientific Frontiers: The Quest for Knowledge Visualization is an excellent book and is highly recommended. The book convincingly outlines general theories conceming cartography, visual communication, and science mapping-especially how metaphors can make a "big picture"simple and useful. The author likewise Shows how the GSA framework is based not only an technical possibilities but indeed also an the visualization principles presented in the beginning chapters. Also, the author does a fine job of explaining why the mapping of scientific frontiers needs a combined effort from a diverse range of underlying disciplines, such as philosophy of science, sociology of science, scientometrics, domain analyses, information visualization, knowledge discovery, and data mining.

0.03299951 = product of:
  0.06599902 = sum of:
    0.032826174 = weight(_text_:science in 3591) [ClassicSimilarity], result of:
      0.032826174 = score(doc=3591,freq=4.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.24694869 = fieldWeight in 3591, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.046875 = fieldNorm(doc=3591)
    0.03317285 = product of:
      0.0663457 = sum of:
        0.0663457 = weight(_text_:network in 3591) [ClassicSimilarity], result of:
          0.0663457 = score(doc=3591,freq=2.0), product of:
            0.22473325 = queryWeight, product of:
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.050463587 = queryNorm
            0.29521978 = fieldWeight in 3591, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.046875 = fieldNorm(doc=3591)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

A multiple-perspective cocitation analysis method is introduced for characterizing and interpreting the structure and dynamics of cocitation clusters. The method facilitates analytic and sense making tasks by integrating network visualization, spectral clustering, automatic cluster labeling, and text summarization. Cocitation networks are decomposed into cocitation clusters. The interpretation of these clusters is augmented by automatic cluster labeling and summarization. The method focuses on the interrelations between a cocitation cluster's members and their citers. The generic method is applied to a three-part analysis of the field of information science as defined by 12 journals published between 1996 and 2008: (a) a comparative author cocitation analysis (ACA), (b) a progressive ACA of a time series of cocitation networks, and (c) a progressive document cocitation analysis (DCA). Results show that the multiple-perspective method increases the interpretability and accountability of both ACA and DCA networks.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.7, S.1386-1409

0.028096987 = product of:
  0.056193974 = sum of:
    0.033503074 = weight(_text_:science in 1200) [ClassicSimilarity], result of:
      0.033503074 = score(doc=1200,freq=6.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.25204095 = fieldWeight in 1200, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1200)
    0.0226909 = weight(_text_:research in 1200) [ClassicSimilarity], result of:
      0.0226909 = score(doc=1200,freq=2.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.15760657 = fieldWeight in 1200, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1200)
  0.5 = coord(2/4)

Abstract

Portfolio analysis of the publication profile of a unit of interest, ranging from individuals and organizations to a scientific field or interdisciplinary programs, aims to inform analysts and decision makers about the position of the unit, where it has been, and where it may go in a complex adaptive environment. A portfolio analysis may aim to identify the gap between the current position of an organization and a goal that it intends to achieve or identify competencies of multiple institutions. We introduce a new visual analytic method for analyzing, comparing, and contrasting characteristics of publication portfolios. The new method introduces a novel design of dual-map thematic overlays on global maps of science. Each publication portfolio can be added as one layer of dual-map overlays over 2 related, but distinct, global maps of science: one for citing journals and the other for cited journals. We demonstrate how the new design facilitates a portfolio analysis in terms of patterns emerging from the distributions of citation threads and the dynamics of trajectories as a function of space and time. We first demonstrate the analysis of portfolios defined on a single source article. Then we contrast publication portfolios of multiple comparable units of interest; namely, colleges in universities and corporate research organizations. We also include examples of overlays of scientific fields. We expect that our method will provide new insights to portfolio analysis.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.2, S.334-351

0.027499594 = product of:
  0.054999188 = sum of:
    0.027355144 = weight(_text_:science in 610) [ClassicSimilarity], result of:
      0.027355144 = score(doc=610,freq=4.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.20579056 = fieldWeight in 610, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0390625 = fieldNorm(doc=610)
    0.027644044 = product of:
      0.055288088 = sum of:
        0.055288088 = weight(_text_:network in 610) [ClassicSimilarity], result of:
          0.055288088 = score(doc=610,freq=2.0), product of:
            0.22473325 = queryWeight, product of:
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.050463587 = queryNorm
            0.2460165 = fieldWeight in 610, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.0390625 = fieldNorm(doc=610)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

Retracting published scientific articles is increasingly common. Retraction is a self-correction mechanism of the scientific community to maintain and safeguard the integrity of scientific literature. However, a retracted article may pose a profound and long-lasting threat to the credibility of the literature. New articles may unknowingly build their work on false claims made in retracted articles. Such dependencies on retracted articles may become implicit and indirect. Consequently, it becomes increasingly important to detect implicit and indirect threats. In this article, our aim is to raise the awareness of the potential threats of retracted articles even after their retraction and demonstrate a visual analytic study of retracted articles with reference to the rest of the literature and how their citations are influenced by their retraction. The context of highly cited retracted articles is visualized in terms of a co-citation network as well as the distribution of articles that have high-order citation dependencies on retracted articles. Survival analyses of time to retraction and postretraction citation are included. Sentences that explicitly cite retracted articles are extracted from full-text articles. Transitions of topics over time are depicted in topic-flow visualizations. We recommend that new visual analytic and science mapping tools should take retracted articles into account and facilitate tasks specifically related to the detection and monitoring of retracted articles.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.2, S.234-253

0.025716392 = product of:
  0.051432785 = sum of:
    0.019343007 = weight(_text_:science in 4600) [ClassicSimilarity], result of:
      0.019343007 = score(doc=4600,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.1455159 = fieldWeight in 4600, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4600)
    0.032089777 = weight(_text_:research in 4600) [ClassicSimilarity], result of:
      0.032089777 = score(doc=4600,freq=4.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.22288933 = fieldWeight in 4600, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4600)
  0.5 = coord(2/4)

Abstract

The practical significances of identifying and accomodating individual differences has been established across a number of fields of research. There is a renewed interest in individual differences due to the advances in virtual environments, especially through far-reaching technologies such as information visualization and 3D graphical user interfaces on the WWW. The effects of individual differences on the use of these new technologies are yet to be found out. More fundamentally, theories and methods developed for the earlier generations of information systems are subject to a close examination of their applicability, efficiency, and effectiveness. In this article, we present a brief historical overview of research in in individual differences in the context of virtual environments. In particular, we highlight the notion of structure in the perception of individual users of an information system and the role of individuals' abilities to recognize and use such structures to perform various information-intensive tasks. Striking the balance between individuals' abilities and the demanding task for detecting, understanding, and utilizing such structures is an emerging theme across the 5 articles in this special issue. We outline the approaches and the major findings of these articles with reference to this central theme

Source

Journal of the American Society for Information Science. 51(2000) no.6, S.499-507

0.025220342 = product of:
  0.050440684 = sum of:
    0.023211608 = weight(_text_:science in 5766) [ClassicSimilarity], result of:
      0.023211608 = score(doc=5766,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.17461908 = fieldWeight in 5766, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.046875 = fieldNorm(doc=5766)
    0.027229078 = weight(_text_:research in 5766) [ClassicSimilarity], result of:
      0.027229078 = score(doc=5766,freq=2.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.18912788 = fieldWeight in 5766, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.046875 = fieldNorm(doc=5766)
  0.5 = coord(2/4)

Abstract

Domain visualization is one of the new research fronts resulted from the proliferation of information visualization, aiming to reveal the essence of a knowledge domain. Information visualization plays an integral role in modeling and representing intellectual structures associated with scientific disciplines. In this article, the domain of computer graphics is visualized based on author cocitation patterns derived from an 18-year span of the prestigious IEEE Computer Graphics and Applications (1982-1999). This domain visualization utilizes a series of visualization and animation techniques, including author cocitation maps, citation time lines, animation of a highdimensional specialty space, and institutional profiles. This approach not only augments traditional domain analysis and the understanding of scientific disciplines, but also produces a persistent and shared knowledge space for researchers to keep track the development of knowledge more effectively. The results of the domain visualization are discussed and triangulated in a broader context of the computer graphics field

Source

Journal of the American Society for Information Science and technology. 52(2001) no.4, S.315-330

0.025220342 = product of:
  0.050440684 = sum of:
    0.023211608 = weight(_text_:science in 1502) [ClassicSimilarity], result of:
      0.023211608 = score(doc=1502,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.17461908 = fieldWeight in 1502, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.046875 = fieldNorm(doc=1502)
    0.027229078 = weight(_text_:research in 1502) [ClassicSimilarity], result of:
      0.027229078 = score(doc=1502,freq=2.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.18912788 = fieldWeight in 1502, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.046875 = fieldNorm(doc=1502)
  0.5 = coord(2/4)

Abstract

Cocitation and co-word methods have long been used to detect and track emerging topics in scientific literature, but both have weaknesses. Recently, while many researchers have adopted generative probabilistic models for topic detection and tracking, few have compared generative probabilistic models with traditional cocitation and co-word methods in terms of their overall performance. In this article, we compare the performance of hierarchical Dirichlet process (HDP), a promising generative probabilistic model, with that of the 2 traditional topic detecting and tracking methods-cocitation analysis and co-word analysis. We visualize and explore the relationships between topics identified by the 3 methods in hierarchical edge bundling graphs and time flow graphs. Our result shows that HDP is more sensitive and reliable than the other 2 methods in both detecting and tracking emerging topics. Furthermore, we demonstrate the important topics and topic evolution trends in the literature of terrorism research with the HDP method.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.10, S.2084-2097

0.020805722 = product of:
  0.041611444 = sum of:
    0.019148601 = weight(_text_:science in 4286) [ClassicSimilarity], result of:
      0.019148601 = score(doc=4286,freq=4.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.1440534 = fieldWeight in 4286, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.02734375 = fieldNorm(doc=4286)
    0.022462843 = weight(_text_:research in 4286) [ClassicSimilarity], result of:
      0.022462843 = score(doc=4286,freq=4.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.15602253 = fieldWeight in 4286, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.02734375 = fieldNorm(doc=4286)
  0.5 = coord(2/4)

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.

Source

Annual review of information science and technology. 37(2003), S.179-258

0.015221517 = product of:
  0.060886066 = sum of:
    0.060886066 = weight(_text_:research in 2275) [ClassicSimilarity], result of:
      0.060886066 = score(doc=2275,freq=10.0), product of:
        0.14397179 = queryWeight, product of:
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.050463587 = queryNorm
        0.42290276 = fieldWeight in 2275, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          2.8529835 = idf(docFreq=6931, maxDocs=44218)
          0.046875 = fieldNorm(doc=2275)
  0.25 = coord(1/4)

Content

We investigate the influence of culture and identity (geographic location) on the constitution of a specific research field. Using as case study the Sloan Digital Sky Survey (SDSS) project in the Astronomy field, we analyzed texts from bibliographic records of publications along three cultural and geographic axes: US only publications, non-US publications and international collaboration. Using three text mining systems (CiteSpace, TermWatch and PEx), we were able to automatically identify the topics specific to each cultural and geographic region as well as isolate the core research topics common to all geographic zones. The results tended to show that US-only and non-US research in this field shared more commonalities with international collaboration than with one another, thus indicating that the former two (US-only and non-US) research focused on rather distinct topics.

0.011728374 = product of:
  0.046913497 = sum of:
    0.046913497 = product of:
      0.093826994 = sum of:
        0.093826994 = weight(_text_:network in 2914) [ClassicSimilarity], result of:
          0.093826994 = score(doc=2914,freq=4.0), product of:
            0.22473325 = queryWeight, product of:
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.050463587 = queryNorm
            0.41750383 = fieldWeight in 2914, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.046875 = fieldNorm(doc=2914)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Describes a study of individuals' spatial navigation strategies and a number of performance and preference measures with regard to the design of a 3D visualisation. The underlying semantic space of the user interface consists of a collection of papers from the 3 most recent ACM SIGCHI conference proceedings, visualised as a virtual reality network. This network was automatically constructed based on semantic similarities derived from latent semantic analysis. The project studied the search strategies and general preferences of 11 subjects who used this system to find papers on various topics. The findings should be valuable for designers and evaluators of 3D user interfaces. The results highlight the importance of structural elements in the design of a semantically based user interface, because search strategies of users relied heavily on these mechanisms in the design. Describes the implications for user interface design based on users' psychological models of a semantic space

0.011728374 = product of:
  0.046913497 = sum of:
    0.046913497 = product of:
      0.093826994 = sum of:
        0.093826994 = weight(_text_:network in 3764) [ClassicSimilarity], result of:
          0.093826994 = score(doc=3764,freq=4.0), product of:
            0.22473325 = queryWeight, product of:
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.050463587 = queryNorm
            0.41750383 = fieldWeight in 3764, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.046875 = fieldNorm(doc=3764)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Introduces a generic approach to the development of hypermedia information systems. Emphasises the role of intrinsic inter-document relationships in structuring and visualising a large hypermedia information space. Illustrates the use of this approach based on 3 types of similarity measurements: hypertext linkage, content similarity and usage patterns. Salient patterns in these relationships are extracted and visualised in a simle and intuitive associated network. The spatial layout of a visualisation is optimised such that closely related documents are placed near to each other and only those intrinsic connections among them are shown to users as automatically generated virtual links. Supports self-organized information space transformation based on usage patterns and othe feedback such that the visual strucutre of the information space is incrementally tailored to users' search and browsing styles

0.009671504 = product of:
  0.038686015 = sum of:
    0.038686015 = weight(_text_:science in 1131) [ClassicSimilarity], result of:
      0.038686015 = score(doc=1131,freq=8.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.2910318 = fieldWeight in 1131, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1131)
  0.25 = coord(1/4)

Abstract

Using the option Analyze Results with the Web of Science, one can directly generate overlays onto global journal maps of science. The maps are based on the 10,000+ journals contained in the Journal Citation Reports (JCR) of the Science and Social Sciences Citation Indices (2011). The disciplinary diversity of the retrieval is measured in terms of Rao-Stirling's "quadratic entropy" (Izsák & Papp, 1995). Since this indicator of interdisciplinarity is normalized between 0 and 1, interdisciplinarity can be compared among document sets and across years, cited or citing. The colors used for the overlays are based on Blondel, Guillaume, Lambiotte, and Lefebvre's (2008) community-finding algorithms operating on the relations among journals included in the JCR. The results can be exported from VOSViewer with different options such as proportional labels, heat maps, or cluster density maps. The maps can also be web-started or animated (e.g., using PowerPoint). The "citing" dimension of the aggregated journal-journal citation matrix was found to provide a more comprehensive description than the matrix based on the cited archive. The relations between local and global maps and their different functions in studying the sciences in terms of journal literatures are further discussed: Local and global maps are based on different assumptions and can be expected to serve different purposes for the explanation.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.12, S.2573-2586

0.006770053 = product of:
  0.027080212 = sum of:
    0.027080212 = weight(_text_:science in 1455) [ClassicSimilarity], result of:
      0.027080212 = score(doc=1455,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.20372227 = fieldWeight in 1455, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1455)
  0.25 = coord(1/4)

Source

Journal of the American Society for Information Science and technology. 54(2003) no.5, S.392-393

0.006770053 = product of:
  0.027080212 = sum of:
    0.027080212 = weight(_text_:science in 1469) [ClassicSimilarity], result of:
      0.027080212 = score(doc=1469,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.20372227 = fieldWeight in 1469, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1469)
  0.25 = coord(1/4)

Source

Journal of the American Society for Information Science and technology. 54(2003) no.5, S.435-446

0.004835752 = product of:
  0.019343007 = sum of:
    0.019343007 = weight(_text_:science in 4603) [ClassicSimilarity], result of:
      0.019343007 = score(doc=4603,freq=2.0), product of:
        0.1329271 = queryWeight, product of:
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.050463587 = queryNorm
        0.1455159 = fieldWeight in 4603, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6341193 = idf(docFreq=8627, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4603)
  0.25 = coord(1/4)

Source

Journal of the American Society for Information Science. 51(2000) no.6, S.529-542