Search (43 results, page 1 of 3)

0.20575523 = product of:
  0.41151047 = sum of:
    0.26271155 = weight(_text_:graphic in 3355) [ClassicSimilarity], result of:
      0.26271155 = score(doc=3355,freq=8.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.8779235 = fieldWeight in 3355, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.046875 = fieldNorm(doc=3355)
    0.14879891 = sum of:
      0.096845575 = weight(_text_:methods in 3355) [ClassicSimilarity], result of:
        0.096845575 = score(doc=3355,freq=8.0), product of:
          0.18168657 = queryWeight, product of:
            4.0204134 = idf(docFreq=2156, maxDocs=44218)
            0.045191016 = queryNorm
          0.53303653 = fieldWeight in 3355, product of:
            2.828427 = tf(freq=8.0), with freq of:
              8.0 = termFreq=8.0
            4.0204134 = idf(docFreq=2156, maxDocs=44218)
            0.046875 = fieldNorm(doc=3355)
      0.051953334 = weight(_text_:22 in 3355) [ClassicSimilarity], result of:
        0.051953334 = score(doc=3355,freq=4.0), product of:
          0.15825124 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.045191016 = 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(2/4)

Date

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

LCSH

Statistics / Graphic methods
Science / Study and teaching / Graphic methods

Subject

Statistics / Graphic methods
Science / Study and teaching / Graphic methods

0.12833637 = product of:
  0.25667274 = sum of:
    0.21672598 = weight(_text_:graphic in 3734) [ClassicSimilarity], result of:
      0.21672598 = score(doc=3734,freq=4.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.72424996 = fieldWeight in 3734, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3734)
    0.039946765 = product of:
      0.07989353 = sum of:
        0.07989353 = weight(_text_:methods in 3734) [ClassicSimilarity], result of:
          0.07989353 = score(doc=3734,freq=4.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.43973273 = fieldWeight in 3734, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3734)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

LCSH

Statistics / Graphic methods

Subject

Statistics / Graphic methods

0.11404774 = product of:
  0.22809549 = sum of:
    0.19581363 = weight(_text_:graphic in 1451) [ClassicSimilarity], result of:
      0.19581363 = score(doc=1451,freq=10.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.65436554 = fieldWeight in 1451, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.03125 = fieldNorm(doc=1451)
    0.032281857 = product of:
      0.064563714 = sum of:
        0.064563714 = weight(_text_:methods in 1451) [ClassicSimilarity], result of:
          0.064563714 = score(doc=1451,freq=8.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.35535768 = fieldWeight in 1451, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.03125 = fieldNorm(doc=1451)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

In his entertaining and informative book "Graphic Discovery", Howard Wainer unlocked the power of graphical display to make complex problems clear. Now he's back with Picturing the Uncertain World, a book that explores how graphs can serve as maps to guide us when the information we have is ambiguous or incomplete. Using a visually diverse sampling of graphical display, from heartrending autobiographical displays of genocide in the Kovno ghetto to the 'Pie Chart of Mystery' in a "New Yorker" cartoon, Wainer illustrates the many ways graphs can be used - and misused - as we try to make sense of an uncertain world. "Picturing the Uncertain World" takes readers on an extraordinary graphical adventure, revealing how the visual communication of data offers answers to vexing questions yet also highlights the measure of uncertainty in almost everything we do. Are cancer rates higher or lower in rural communities? How can you know how much money to sock away for retirement when you don't know when you'll die? And where exactly did nineteenth-century novelists get their ideas? These are some of the fascinating questions Wainer invites readers to consider. Along the way he traces the origins and development of graphical display, from William Playfair, who pioneered the use of graphs in the eighteenth century, to instances today where the public has been misled through poorly designed graphs. We live in a world full of uncertainty, yet it is within our grasp to take its measure. Read "Picturing the Uncertain World" and learn how.

LCSH

Uncertainty (Information theory) / Graphic methods
Communication in science / Graphic methods

Subject

Uncertainty (Information theory) / Graphic methods
Communication in science / Graphic methods

0.08749021 = product of:
  0.17498042 = sum of:
    0.15480426 = weight(_text_:graphic in 1463) [ClassicSimilarity], result of:
      0.15480426 = score(doc=1463,freq=4.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.51732135 = fieldWeight in 1463, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1463)
    0.020176161 = product of:
      0.040352322 = sum of:
        0.040352322 = weight(_text_:methods in 1463) [ClassicSimilarity], result of:
          0.040352322 = score(doc=1463,freq=2.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.22209854 = fieldWeight in 1463, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1463)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

The use of graphical representations is very common in information technology and engineering. Although these same tools could be applied effectively in other areas, they are not used because they are hardly known or are completely unheard of. This article aims to discuss the results of the experimentation carried out on graphical approaches to knowledge representation during research, analysis and problem-solving in the health care sector. The experimentation was carried out on conceptual mapping and Petri Nets, developed collaboratively online with the aid of the CMapTool and WoPeD graphic applications. Two distinct professional communities have been involved in the research, both pertaining to the Local Health Units in Tuscany. One community is made up of head physicians and health care managers whilst the other is formed by technical staff from the Department of Nutrition and Food Hygiene. It emerged from the experimentation that concept maps arc considered more effective in analyzing knowledge domain related to the problem to be faced (description of what it is). On the other hand, Petri Nets arc more effective in studying and formalizing its possible solutions (description of what to do to). For the same reason, those involved in the experimentation have proposed the complementary rather than alternative use of the two knowledge representation methods as a support for professional problem-solving.

0.05473157 = product of:
  0.21892628 = sum of:
    0.21892628 = weight(_text_:graphic in 1101) [ClassicSimilarity], result of:
      0.21892628 = score(doc=1101,freq=2.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.7316029 = fieldWeight in 1101, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.078125 = fieldNorm(doc=1101)
  0.25 = coord(1/4)

0.0383121 = product of:
  0.1532484 = sum of:
    0.1532484 = weight(_text_:graphic in 2620) [ClassicSimilarity], result of:
      0.1532484 = score(doc=2620,freq=2.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.51212204 = fieldWeight in 2620, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2620)
  0.25 = coord(1/4)

Abstract

Describes the use of concept maps as one of the semantic tools employed in the ADEPT (Alexandria Digital Earth Prototype) Digital Learning Environment (DLE) for teaching undergraduate classes. The graphic representation of the conceptualizations is derived from the knowledge in stronglystructured models (SSMs) of concepts represented in one or more knowledge bases. Such knowledge bases function as a source of "reference" information about concepts in a given context, including information about their scientific representation, scientific semantics, manipulation, and interrelationships to other concepts.

0.037431013 = product of:
  0.074862026 = sum of:
    0.06567789 = weight(_text_:graphic in 3035) [ClassicSimilarity], result of:
      0.06567789 = score(doc=3035,freq=2.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.21948087 = fieldWeight in 3035, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.0234375 = fieldNorm(doc=3035)
    0.009184138 = product of:
      0.018368276 = sum of:
        0.018368276 = weight(_text_:22 in 3035) [ClassicSimilarity], result of:
          0.018368276 = score(doc=3035,freq=2.0), product of:
            0.15825124 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045191016 = 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)
  0.5 = coord(2/4)

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.

0.032838944 = product of:
  0.13135578 = sum of:
    0.13135578 = weight(_text_:graphic in 919) [ClassicSimilarity], result of:
      0.13135578 = score(doc=919,freq=2.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.43896174 = fieldWeight in 919, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.046875 = fieldNorm(doc=919)
  0.25 = coord(1/4)

Abstract

Document retrieval is a highly interactive process dealing with large amounts of information. Visual representations can provide both a means for managing the complexity of large information structures and an interface style well suited to interactive manipulation. The system we have designed utilizes visually displayed graphic structures and a direct manipulation interface style to supply an integrated environment for retrieval. A common visually displayed network structure is used for query, document content, and term relations. A query can be modified through direct manipulation of its visual form by incorporating terms from any other information structure the system displays. An associative thesaurus of terms and an inter-document network provide information about a document collection that can complement other retrieval aids. Visualization of these large data structures makes use of fisheye views and overview diagrams to help overcome some of the inherent difficulties of orientation and navigation in large information structures.

0.02189263 = product of:
  0.08757052 = sum of:
    0.08757052 = weight(_text_:graphic in 3646) [ClassicSimilarity], result of:
      0.08757052 = score(doc=3646,freq=2.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.29264116 = fieldWeight in 3646, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.03125 = fieldNorm(doc=3646)
  0.25 = coord(1/4)

0.02189263 = product of:
  0.08757052 = sum of:
    0.08757052 = weight(_text_:graphic in 5215) [ClassicSimilarity], result of:
      0.08757052 = score(doc=5215,freq=2.0), product of:
        0.29924196 = queryWeight, product of:
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.045191016 = queryNorm
        0.29264116 = fieldWeight in 5215, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          6.6217136 = idf(docFreq=159, maxDocs=44218)
          0.03125 = fieldNorm(doc=5215)
  0.25 = coord(1/4)

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.

0.021289835 = product of:
  0.08515934 = sum of:
    0.08515934 = sum of:
      0.048422787 = weight(_text_:methods in 3693) [ClassicSimilarity], result of:
        0.048422787 = score(doc=3693,freq=2.0), product of:
          0.18168657 = queryWeight, product of:
            4.0204134 = idf(docFreq=2156, maxDocs=44218)
            0.045191016 = queryNorm
          0.26651827 = fieldWeight in 3693, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.0204134 = idf(docFreq=2156, maxDocs=44218)
            0.046875 = fieldNorm(doc=3693)
      0.03673655 = weight(_text_:22 in 3693) [ClassicSimilarity], result of:
        0.03673655 = score(doc=3693,freq=2.0), product of:
          0.15825124 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.045191016 = queryNorm
          0.23214069 = fieldWeight in 3693, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=3693)
  0.25 = coord(1/4)

Date

22. 7.2010 19:36:46

0.011278818 = product of:
  0.045115273 = sum of:
    0.045115273 = product of:
      0.09023055 = sum of:
        0.09023055 = weight(_text_:methods in 617) [ClassicSimilarity], result of:
          0.09023055 = score(doc=617,freq=10.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.4966275 = fieldWeight in 617, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0390625 = fieldNorm(doc=617)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

The study adopts a naturalistic approach to investigate users' interaction with a browsable MeSH (medical subject headings) display designed to facilitate query construction for the PubMed bibliographic database. The purpose of the study is twofold: first, to test the usefulness of a browsable interface utilizing the principle of faceted classification; and second, to investigate users' preferred query submission methods in different problematic situations. An interface that incorporated multiple query submission methods - the conventional single-line query box as well as methods associated the faceted classification display was constructed. Participants' interactions with the interface were monitored remotely over a period of 10 weeks; information about their problematic situations and information retrieval behaviors were also collected during this time. The traditional controlled experiment was not adequate in answering the author's research questions; hence, the author provides his rationale for a naturalistic approach. The study's findings show that there is indeed a selective compatibility between query submission methods provided by the MeSH display and users' problematic situations. The query submission methods associated with the display were found to be the preferred search tools when users' information needs were vague and the search topics unfamiliar. The findings support the theoretical proposition that users engaging in an information retrieval process with a variety of problematic situations need different approaches. The author argues that rather than treat the information retrieval system as a general purpose tool, more attention should be given to the interaction between the functionality of the tool and the characteristics of users' problematic situations.

0.009986691 = product of:
  0.039946765 = sum of:
    0.039946765 = product of:
      0.07989353 = sum of:
        0.07989353 = weight(_text_:methods in 1528) [ClassicSimilarity], result of:
          0.07989353 = score(doc=1528,freq=4.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.43973273 = fieldWeight in 1528, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1528)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Statistical methods for automated document indexing are becoming an alternative to the manual assignment of keywords. We argue that the quality of the thesaurus used as a basis for indexing in regard to its ability to adequately cover the contents to be indexed and as a basis for the specific indexing method used is of crucial importance in automatic indexing. We present an interactive tool for thesaurus evaluation that is based on a combination of statistical measures and appropriate visualisation techniques that supports the detection of potential problems in a thesaurus. We describe the methods used and show that the tool supports the detection and correction of errors, leading to a better indexing result.

0.00876806 = product of:
  0.03507224 = sum of:
    0.03507224 = sum of:
      0.022826722 = weight(_text_:methods in 1789) [ClassicSimilarity], result of:
        0.022826722 = score(doc=1789,freq=4.0), product of:
          0.18168657 = queryWeight, product of:
            4.0204134 = idf(docFreq=2156, maxDocs=44218)
            0.045191016 = queryNorm
          0.12563792 = fieldWeight in 1789, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            4.0204134 = idf(docFreq=2156, maxDocs=44218)
            0.015625 = fieldNorm(doc=1789)
      0.012245518 = weight(_text_:22 in 1789) [ClassicSimilarity], result of:
        0.012245518 = score(doc=1789,freq=2.0), product of:
          0.15825124 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.045191016 = queryNorm
          0.07738023 = fieldWeight in 1789, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.015625 = fieldNorm(doc=1789)
  0.25 = coord(1/4)

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.

0.0085600205 = product of:
  0.034240082 = sum of:
    0.034240082 = product of:
      0.068480164 = sum of:
        0.068480164 = weight(_text_:methods in 1847) [ClassicSimilarity], result of:
          0.068480164 = score(doc=1847,freq=4.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.37691376 = fieldWeight in 1847, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.046875 = fieldNorm(doc=1847)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

The present study reports on the information seeking processes in a visual context, referred to throughout as visual information seeking. This study synthesizes research throughout different, yet complementary, areas, each capable of contributing findings and understanding to visual information seeking. Methods previously applied for examining the visual information seeking process are reviewed, including interactive experiments, surveys, and various qualitative approaches. The methods and resulting findings are presented and structured according to generalized phases of existing information seeking models, which include the needs, actions, and assessments of users. A review of visual information needs focuses on need and thus query formulation; user actions, as reviewed, centers on search and browse behaviors and the observed trends, concluded by a survey of users' assessments of visual information as part of the interactive process. This separate examination, specific to a visual context, is significant; visual information can influence outcomes in an interactive process and presents variations in the types of needs, tasks, considerations, and decisions of users, as compared to information seeking in other contexts.

0.0076534487 = product of:
  0.030613795 = sum of:
    0.030613795 = product of:
      0.06122759 = sum of:
        0.06122759 = weight(_text_:22 in 3406) [ClassicSimilarity], result of:
          0.06122759 = score(doc=3406,freq=2.0), product of:
            0.15825124 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045191016 = 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)
  0.25 = coord(1/4)

Date

30. 5.2010 16:22:35

0.0076534487 = product of:
  0.030613795 = sum of:
    0.030613795 = product of:
      0.06122759 = sum of:
        0.06122759 = weight(_text_:22 in 2755) [ClassicSimilarity], result of:
          0.06122759 = score(doc=2755,freq=2.0), product of:
            0.15825124 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045191016 = 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)
  0.25 = coord(1/4)

Date

1. 2.2016 18:25:22

0.0071333502 = product of:
  0.028533401 = sum of:
    0.028533401 = product of:
      0.057066802 = sum of:
        0.057066802 = weight(_text_:methods in 3124) [ClassicSimilarity], result of:
          0.057066802 = score(doc=3124,freq=4.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.31409478 = fieldWeight in 3124, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3124)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

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.

0.0071333502 = product of:
  0.028533401 = sum of:
    0.028533401 = product of:
      0.057066802 = sum of:
        0.057066802 = weight(_text_:methods in 3651) [ClassicSimilarity], result of:
          0.057066802 = score(doc=3651,freq=4.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.31409478 = fieldWeight in 3651, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3651)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

In the information science literature, recent studies have used patent databases and patent classification information to construct network maps of patent technology classes. In such a patent technology map, almost all pairs of technology classes are connected, whereas most of the connections between them are extremely weak. This observation suggests the possibility of filtering the patent network map by removing weak links. However, removing links may reduce the explanatory power of the network on inventor or organization diversification. The network links may explain the patent portfolio diversification paths of inventors and inventing organizations. We measure the diversification explanatory power of the patent network map, and present a method to objectively choose an optimal tradeoff between explanatory power and removing weak links. We show that this method can remove a degree of arbitrariness compared with previous filtering methods based on arbitrary thresholds, and also identify previous filtering methods that created filters outside the optimal tradeoff. The filtered map aims to aid in network visualization analyses of the technological diversification of inventors, organizations, and other innovation agents, and potential foresight analysis. Such applications to a prolific inventor (Leonard Forbes) and company (Google) are demonstrated.

0.0071333502 = product of:
  0.028533401 = sum of:
    0.028533401 = product of:
      0.057066802 = sum of:
        0.057066802 = weight(_text_:methods in 687) [ClassicSimilarity], result of:
          0.057066802 = score(doc=687,freq=4.0), product of:
            0.18168657 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.045191016 = queryNorm
            0.31409478 = fieldWeight in 687, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.0390625 = fieldNorm(doc=687)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Purpose The purpose of this paper is to examine whether and how a methodological coupling of visualisations of trace data and interview methods can be utilised for information practices studies. Design/methodology/approach Trace data visualisation enquiry is suggested as the coupling of visualising exported data from an information system and using these visualisations as basis for interview guides and elicitation in information practices research. The methodology is illustrated and applied through a small-scale empirical study of a citizen science project. Findings The study found that trace data visualisation enquiry enabled fine-grained investigations of temporal aspects of information practices and to compare and explore temporal and geographical aspects of practices. Moreover, the methodology made possible inquiries for understanding information practices through trace data that were discussed through elicitation with participants. The study also found that it can aid a researcher of gaining a simultaneous overarching and close picture of information practices, which can lead to theoretical and methodological implications for information practices research. Originality/value Trace data visualisation enquiry extends current methods for investigating information practices as it enables focus to be placed on the traces of practices as recorded through interactions with information systems and study participants' accounts of activities.