Search (177 results, page 2 of 9)

0.010058529 = product of:
  0.020117057 = sum of:
    0.020117057 = product of:
      0.030175585 = sum of:
        0.0053772116 = weight(_text_:a in 2659) [ClassicSimilarity], result of:
          0.0053772116 = score(doc=2659,freq=8.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.10191591 = fieldWeight in 2659, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.03125 = fieldNorm(doc=2659)
        0.024798373 = weight(_text_:22 in 2659) [ClassicSimilarity], result of:
          0.024798373 = score(doc=2659,freq=2.0), product of:
            0.16023713 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045758117 = queryNorm
            0.15476047 = fieldWeight in 2659, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=2659)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Abstract

The Library of Congress Subject Headings (LCSH) has been developed over the course of more than a century, predating the semantic web by some time. Until the 1986, the only concept-toconcept relationship available was an undifferentiated "See Also" reference, which was used for both associative (RT) and hierarchical (BT/NT) connections. In that year, in preparation for the first release of the headings in machine readable MARC Authorities form, an attempt was made to automatically convert these "See Also" links into the standardized thesaural relations. Unfortunately, the rule used to determine the type of reference to generate relied on the presence of symmetric links to detect associatively related terms; "See Also" references that were only present in one of the related terms were assumed to be hierarchical. This left the process vulnerable to inconsistent use of references in the pre-conversion data, with a marked bias towards promoting relationships to hierarchical status. The Library of Congress was aware that the results of the conversion contained many inconsistencies, and intended to validate and correct the results over the course of time. Unfortunately, twenty years later, less than 40% of the converted records have been evaluated. The converted records, being the earliest encountered during the Library's cataloging activities, represent the most basic concepts within LCSH; errors in the syndetic structure for these records affect far more subordinate concepts than those nearer the periphery. Worse, a policy of patterning new headings after pre-existing ones leads to structural errors arising from the conversion process being replicated in these newer headings, perpetuating and exacerbating the errors. As the LCSH prepares for its second great conversion, from MARC to SKOS, it is critical to address these structural problems. As part of the work on converting the headings into SKOS, I have experimented with different visualizations of the tangled web of broader terms embedded in LCSH. This poster illustrates several of these renderings, shows how they can help users to judge which relationships might not be correct, and shows just exactly how Doorbells and Mammals are related.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

Type

a

0.010043396 = product of:
  0.020086791 = sum of:
    0.020086791 = product of:
      0.030130185 = sum of:
        0.011406789 = weight(_text_:a in 3205) [ClassicSimilarity], result of:
          0.011406789 = score(doc=3205,freq=16.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.2161963 = fieldWeight in 3205, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=3205)
        0.018723397 = weight(_text_:h in 3205) [ClassicSimilarity], result of:
          0.018723397 = score(doc=3205,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.16469726 = fieldWeight in 3205, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.046875 = fieldNorm(doc=3205)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Abstract

The goal of Open Knowledge Maps is to create a visual interface to the world's scientific knowledge. The base for this visual interface consists of so-called knowledge maps, which enable the exploration of existing knowledge and the discovery of new knowledge. Our open source knowledge mapping software applies a mixture of summarization techniques and similarity measures on article metadata, which are iteratively chained together. After processing, the representation is saved in a database for use in a web visualization. In the future, we want to create a space for collective knowledge mapping that brings together individuals and communities involved in exploration and discovery. We want to enable people to guide each other in their discovery by collaboratively annotating and modifying the automatically created maps.

Source

027.7 Zeitschrift für Bibliothekskultur. 4(2016), H.2

Type

a

0.009819239 = product of:
  0.019638479 = sum of:
    0.019638479 = product of:
      0.029457718 = sum of:
        0.010858939 = weight(_text_:a in 3035) [ClassicSimilarity], result of:
          0.010858939 = score(doc=3035,freq=58.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.20581275 = fieldWeight in 3035, product of:
              7.615773 = tf(freq=58.0), with freq of:
                58.0 = termFreq=58.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0234375 = fieldNorm(doc=3035)
        0.01859878 = weight(_text_:22 in 3035) [ClassicSimilarity], result of:
          0.01859878 = score(doc=3035,freq=2.0), product of:
            0.16023713 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045758117 = 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)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Abstract

A PICTURE is said to be worth a thousand words. That metaphor might be expected to pertain a fortiori in the case of scientific papers, where a figure can brilliantly illuminate an idea that might otherwise be baffling. Papers with figures in them should thus be easier to grasp than those without. They should therefore reach larger audiences and, in turn, be more influential simply by virtue of being more widely read. But are they?

Content

Bill Howe and his colleagues at the University of Washington, in Seattle, decided to find out. First, they trained a computer algorithm to distinguish between various sorts of figures-which they defined as diagrams, equations, photographs, plots (such as bar charts and scatter graphs) and tables. They exposed their algorithm to between 400 and 600 images of each of these types of figure until it could distinguish them with an accuracy greater than 90%. Then they set it loose on the more-than-650,000 papers (containing more than 10m figures) stored on PubMed Central, an online archive of biomedical-research articles. To measure each paper's influence, they calculated its article-level Eigenfactor score-a modified version of the PageRank algorithm Google uses to provide the most relevant results for internet searches. Eigenfactor scoring gives a better measure than simply noting the number of times a paper is cited elsewhere, because it weights citations by their influence. A citation in a paper that is itself highly cited is worth more than one in a paper that is not.
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.

Language

a

Type

a

0.008929739 = product of:
  0.017859478 = sum of:
    0.017859478 = product of:
      0.026789214 = sum of:
        0.008065818 = weight(_text_:a in 4969) [ClassicSimilarity], result of:
          0.008065818 = score(doc=4969,freq=8.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.15287387 = fieldWeight in 4969, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=4969)
        0.018723397 = weight(_text_:h in 4969) [ClassicSimilarity], result of:
          0.018723397 = score(doc=4969,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.16469726 = fieldWeight in 4969, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.046875 = fieldNorm(doc=4969)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Abstract

This study proposes an approach for visualizing knowledge structures that creates a "research-focused parallelship network," "keyword co-occurrence network," and a knowledge map to visualize Sci-Tech policy research structure. A total of 1,125 Sci-Tech policy-related papers (873 journal papers [78%], 205 conference papers [18%], and 47 review papers [4%]) have been retrieved from the Web of Science database for quantitative analysis and mapping. Different network and contour maps based on these 1,125 papers can be constructed by choosing different information as the main actor, such as the paper title, the institute, the country, or the author keywords, to reflect Sci-Tech policy research structures in micro-, meso-, and macro-levels, respectively. The quantitative way of exploring Sci-Tech policy research papers is investigated to unveil important or emerging Sci-Tech policy implications as well as to demonstrate the dynamics and visualization of the evolution of Sci-Tech policy research.

Type

a

0.008849675 = product of:
  0.01769935 = sum of:
    0.01769935 = product of:
      0.026549023 = sum of:
        0.0047050603 = weight(_text_:a in 3432) [ClassicSimilarity], result of:
          0.0047050603 = score(doc=3432,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.089176424 = fieldWeight in 3432, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3432)
        0.021843962 = weight(_text_:h in 3432) [ClassicSimilarity], result of:
          0.021843962 = score(doc=3432,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.19214681 = fieldWeight in 3432, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3432)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

nfd Information - Wissenschaft und Praxis. 50(1999) H.2, S.79-86

Type

a

0.008849675 = product of:
  0.01769935 = sum of:
    0.01769935 = product of:
      0.026549023 = sum of:
        0.0047050603 = weight(_text_:a in 399) [ClassicSimilarity], result of:
          0.0047050603 = score(doc=399,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.089176424 = fieldWeight in 399, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=399)
        0.021843962 = weight(_text_:h in 399) [ClassicSimilarity], result of:
          0.021843962 = score(doc=399,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.19214681 = fieldWeight in 399, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0546875 = fieldNorm(doc=399)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

Information - Wissenschaft und Praxis. 58(2007) H.3, S.149-158

Type

a

0.008849675 = product of:
  0.01769935 = sum of:
    0.01769935 = product of:
      0.026549023 = sum of:
        0.0047050603 = weight(_text_:a in 2615) [ClassicSimilarity], result of:
          0.0047050603 = score(doc=2615,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.089176424 = fieldWeight in 2615, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2615)
        0.021843962 = weight(_text_:h in 2615) [ClassicSimilarity], result of:
          0.021843962 = score(doc=2615,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.19214681 = fieldWeight in 2615, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2615)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 68(2015) H.3/4, S.416-438

Type

a

0.0077059045 = product of:
  0.015411809 = sum of:
    0.015411809 = product of:
      0.023117714 = sum of:
        0.007514882 = weight(_text_:a in 3366) [ClassicSimilarity], result of:
          0.007514882 = score(doc=3366,freq=10.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.14243183 = fieldWeight in 3366, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3366)
        0.015602832 = weight(_text_:h in 3366) [ClassicSimilarity], result of:
          0.015602832 = score(doc=3366,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.13724773 = fieldWeight in 3366, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3366)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Abstract

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.

Type

a

0.007585435 = product of:
  0.01517087 = sum of:
    0.01517087 = product of:
      0.022756305 = sum of:
        0.004032909 = weight(_text_:a in 3182) [ClassicSimilarity], result of:
          0.004032909 = score(doc=3182,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.07643694 = fieldWeight in 3182, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=3182)
        0.018723397 = weight(_text_:h in 3182) [ClassicSimilarity], result of:
          0.018723397 = score(doc=3182,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.16469726 = fieldWeight in 3182, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.046875 = fieldNorm(doc=3182)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

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

Type

a

0.007585435 = product of:
  0.01517087 = sum of:
    0.01517087 = product of:
      0.022756305 = sum of:
        0.004032909 = weight(_text_:a in 5953) [ClassicSimilarity], result of:
          0.004032909 = score(doc=5953,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.07643694 = fieldWeight in 5953, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=5953)
        0.018723397 = weight(_text_:h in 5953) [ClassicSimilarity], result of:
          0.018723397 = score(doc=5953,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.16469726 = fieldWeight in 5953, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.046875 = fieldNorm(doc=5953)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

Information - Wissenschaft und Praxis. 57(2006) H.5, S.249-254

Type

a

0.007585435 = product of:
  0.01517087 = sum of:
    0.01517087 = product of:
      0.022756305 = sum of:
        0.004032909 = weight(_text_:a in 1022) [ClassicSimilarity], result of:
          0.004032909 = score(doc=1022,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.07643694 = fieldWeight in 1022, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=1022)
        0.018723397 = weight(_text_:h in 1022) [ClassicSimilarity], result of:
          0.018723397 = score(doc=1022,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.16469726 = fieldWeight in 1022, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.046875 = fieldNorm(doc=1022)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

Information - Wissenschaft und Praxis. 64(2013) H.4, S.209-213

Type

a

0.007232859 = product of:
  0.014465718 = sum of:
    0.014465718 = product of:
      0.04339715 = sum of:
        0.04339715 = weight(_text_:22 in 2500) [ClassicSimilarity], result of:
          0.04339715 = score(doc=2500,freq=2.0), product of:
            0.16023713 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045758117 = queryNorm
            0.2708308 = fieldWeight in 2500, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2500)
      0.33333334 = coord(1/3)
  0.5 = coord(1/2)

Date

30. 1.2007 18:22:41

0.007058808 = product of:
  0.014117616 = sum of:
    0.014117616 = product of:
      0.021176424 = sum of:
        0.010254442 = weight(_text_:a in 4276) [ClassicSimilarity], result of:
          0.010254442 = score(doc=4276,freq=38.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.19435552 = fieldWeight in 4276, product of:
              6.164414 = tf(freq=38.0), with freq of:
                38.0 = termFreq=38.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.02734375 = fieldNorm(doc=4276)
        0.010921981 = weight(_text_:h in 4276) [ClassicSimilarity], result of:
          0.010921981 = score(doc=4276,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.096073404 = fieldWeight in 4276, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.02734375 = fieldNorm(doc=4276)
      0.6666667 = coord(2/3)
  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.
Visualization can be classified as scientific visualization, software visualization, or information visualization. Although the data differ, the underlying techniques have much in common. They use the same elements (visual cues) and follow the same rules of combining visual cues to deliver patterns. They all involve understanding human perception (Encarnacao, Foley, Bryson, & Feiner, 1994) and require domain knowledge (Tufte, 1990). Because most decisions are based an unstructured information, such as text documents, Web pages, or e-mail messages, this chapter focuses an the visualization of unstructured textual documents. The chapter reviews information visualization techniques developed over the last decade and examines how they have been applied in different domains. The first section provides the background by describing visualization history and giving overviews of scientific, software, and information visualization as well as the perceptual aspects of visualization. The next section assesses important visualization techniques that convert abstract information into visual objects and facilitate navigation through displays an a computer screen. It also explores information analysis algorithms that can be applied to identify or extract salient visualizable structures from collections of information. Information visualization systems that integrate different types of technologies to address problems in different domains are then surveyed; and we move an to a survey and critique of visualization system evaluation studies. The chapter concludes with a summary and identification of future research directions.

Type

a

0.0067852205 = product of:
  0.013570441 = sum of:
    0.013570441 = product of:
      0.02035566 = sum of:
        0.0047528287 = weight(_text_:a in 566) [ClassicSimilarity], result of:
          0.0047528287 = score(doc=566,freq=4.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.090081796 = fieldWeight in 566, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=566)
        0.015602832 = weight(_text_:h in 566) [ClassicSimilarity], result of:
          0.015602832 = score(doc=566,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.13724773 = fieldWeight in 566, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0390625 = fieldNorm(doc=566)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

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

Type

a

0.0064179376 = product of:
  0.012835875 = sum of:
    0.012835875 = product of:
      0.019253813 = sum of:
        0.0068546273 = weight(_text_:a in 1789) [ClassicSimilarity], result of:
          0.0068546273 = score(doc=1789,freq=52.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.12991782 = fieldWeight in 1789, product of:
              7.2111025 = tf(freq=52.0), with freq of:
                52.0 = termFreq=52.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.015625 = fieldNorm(doc=1789)
        0.012399186 = weight(_text_:22 in 1789) [ClassicSimilarity], result of:
          0.012399186 = score(doc=1789,freq=2.0), product of:
            0.16023713 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045758117 = 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)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

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.
In 13 chapters, Part Two provides an introduction to KDD, an overview of data mining techniques, and examples of the usefulness of data model visualizations. The importance of visualization throughout the KDD process is stressed in many of the chapters. In particular, the need for measures of visualization effectiveness, benchmarking for identifying best practices, and the use of standardized sample data sets is convincingly presented. Many of the important data mining approaches are discussed in this complementary context. Cluster and outlier detection, classification techniques, and rule discovery algorithms are presented as the basic techniques common to the KDD process. The potential effectiveness of using visualization in the data modeling process are illustrated in chapters focused an using visualization for helping users understand the KDD process, ask questions and form hypotheses about their data, and evaluate the accuracy and veracity of their results. The 11 chapters of Part Three provide an overview of the KDD process and successful approaches to integrating KDD, data mining, and visualization in complementary domains. Rhodes (Chapter 21) begins this section with an excellent overview of the relation between the KDD process and data mining techniques. He states that the "primary goals of data mining are to describe the existing data and to predict the behavior or characteristics of future data of the same type" (p. 281). These goals are met by data mining tasks such as classification, regression, clustering, summarization, dependency modeling, and change or deviation detection. Subsequent chapters demonstrate how visualization can aid users in the interactive process of knowledge discovery by graphically representing the results from these iterative tasks. Finally, examples of the usefulness of integrating visualization and data mining tools in the domain of business, imagery and text mining, and massive data sets are provided. This text concludes with a thorough and useful 17-page index and lengthy yet integrating 17-page summary of the academic and industrial backgrounds of the contributing authors. A 16-page set of color inserts provide a better representation of the visualizations discussed, and a URL provided suggests that readers may view all the book's figures in color on-line, although as of this submission date it only provides access to a summary of the book and its contents. The overall contribution of this work is its focus an bridging two distinct areas of research, making it a valuable addition to the Morgan Kaufmann Series in Database Management Systems. The editors of this text have met their main goal of providing the first textbook integrating knowledge discovery, data mining, and visualization. Although it contributes greatly to our under- standing of the development and current state of the field, a major weakness of this text is that there is no concluding chapter to discuss the contributions of the sum of these contributed papers or give direction to possible future areas of research. "Integration of expertise between two different disciplines is a difficult process of communication and reeducation. Integrating data mining and visualization is particularly complex because each of these fields in itself must draw an a wide range of research experience" (p. 300). Although this work contributes to the crossdisciplinary communication needed to advance visualization in KDD, a more formal call for an interdisciplinary research agenda in a concluding chapter would have provided a more satisfying conclusion to a very good introductory text.
With contributors almost exclusively from the computer science field, the intended audience of this work is heavily slanted towards a computer science perspective. However, it is highly readable and provides introductory material that would be useful to information scientists from a variety of domains. Yet, much interesting work in information visualization from other fields could have been included giving the work more of an interdisciplinary perspective to complement their goals of integrating work in this area. Unfortunately, many of the application chapters are these, shallow, and lack complementary illustrations of visualization techniques or user interfaces used. However, they do provide insight into the many applications being developed in this rapidly expanding field. The authors have successfully put together a highly useful reference text for the data mining and information visualization communities. Those interested in a good introduction and overview of complementary research areas in these fields will be satisfied with this collection of papers. The focus upon integrating data visualization with data mining complements texts in each of these fields, such as Advances in Knowledge Discovery and Data Mining (Fayyad et al., MIT Press) and Readings in Information Visualization: Using Vision to Think (Card et. al., Morgan Kauffman). This unique work is a good starting point for future interaction between researchers in the fields of data visualization and data mining and makes a good accompaniment for a course focused an integrating these areas or to the main reference texts in these fields."

0.0063211964 = product of:
  0.012642393 = sum of:
    0.012642393 = product of:
      0.018963588 = sum of:
        0.0033607571 = weight(_text_:a in 3467) [ClassicSimilarity], result of:
          0.0033607571 = score(doc=3467,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.06369744 = fieldWeight in 3467, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3467)
        0.015602832 = weight(_text_:h in 3467) [ClassicSimilarity], result of:
          0.015602832 = score(doc=3467,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.13724773 = fieldWeight in 3467, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3467)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

Datenbank Spektrum. 17(2017) H.1, S.53-60

Type

a

0.0063211964 = product of:
  0.012642393 = sum of:
    0.012642393 = product of:
      0.018963588 = sum of:
        0.0033607571 = weight(_text_:a in 3912) [ClassicSimilarity], result of:
          0.0033607571 = score(doc=3912,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.06369744 = fieldWeight in 3912, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3912)
        0.015602832 = weight(_text_:h in 3912) [ClassicSimilarity], result of:
          0.015602832 = score(doc=3912,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.13724773 = fieldWeight in 3912, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3912)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 70(2017) H.2, S.179-199

Type

a

0.0063211964 = product of:
  0.012642393 = sum of:
    0.012642393 = product of:
      0.018963588 = sum of:
        0.0033607571 = weight(_text_:a in 5702) [ClassicSimilarity], result of:
          0.0033607571 = score(doc=5702,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.06369744 = fieldWeight in 5702, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5702)
        0.015602832 = weight(_text_:h in 5702) [ClassicSimilarity], result of:
          0.015602832 = score(doc=5702,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.13724773 = fieldWeight in 5702, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5702)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Source

Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 72(2019) H.2-4, S.460-477

Type

a

0.0063211964 = product of:
  0.012642393 = sum of:
    0.012642393 = product of:
      0.018963588 = sum of:
        0.0033607571 = weight(_text_:a in 791) [ClassicSimilarity], result of:
          0.0033607571 = score(doc=791,freq=2.0), product of:
            0.052761257 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045758117 = queryNorm
            0.06369744 = fieldWeight in 791, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=791)
        0.015602832 = weight(_text_:h in 791) [ClassicSimilarity], result of:
          0.015602832 = score(doc=791,freq=2.0), product of:
            0.113683715 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045758117 = queryNorm
            0.13724773 = fieldWeight in 791, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0390625 = fieldNorm(doc=791)
      0.6666667 = coord(2/3)
  0.5 = coord(1/2)

Type

a

0.0061995937 = product of:
  0.012399187 = sum of:
    0.012399187 = product of:
      0.03719756 = sum of:
        0.03719756 = weight(_text_:22 in 1781) [ClassicSimilarity], result of:
          0.03719756 = score(doc=1781,freq=2.0), product of:
            0.16023713 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045758117 = queryNorm
            0.23214069 = fieldWeight in 1781, 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=1781)
      0.33333334 = coord(1/3)
  0.5 = coord(1/2)

Date

22. 3.2008 14:35:21