Search (878 results, page 3 of 44)

0.036885202 = product of:
  0.18442601 = sum of:
    0.18442601 = weight(_text_:index in 1087) [ClassicSimilarity], result of:
      0.18442601 = score(doc=1087,freq=4.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.8193307 = fieldWeight in 1087, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.09375 = fieldNorm(doc=1087)
  0.2 = coord(1/5)

Object

h-index

0.036885202 = product of:
  0.18442601 = sum of:
    0.18442601 = weight(_text_:index in 1597) [ClassicSimilarity], result of:
      0.18442601 = score(doc=1597,freq=4.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.8193307 = fieldWeight in 1597, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.09375 = fieldNorm(doc=1597)
  0.2 = coord(1/5)

Object

h-index

0.036885202 = product of:
  0.18442601 = sum of:
    0.18442601 = weight(_text_:index in 1864) [ClassicSimilarity], result of:
      0.18442601 = score(doc=1864,freq=4.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.8193307 = fieldWeight in 1864, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.09375 = fieldNorm(doc=1864)
  0.2 = coord(1/5)

Object

g-index

0.036043115 = product of:
  0.18021557 = sum of:
    0.18021557 = weight(_text_:index in 1053) [ClassicSimilarity], result of:
      0.18021557 = score(doc=1053,freq=22.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.8006254 = fieldWeight in 1053, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1053)
  0.2 = coord(1/5)

Abstract

It was argued recently that the g-index is a measure of a researcher's specific impact (i.e., impact per paper) as much as it is a measure of overall impact. While this is true for the productive "core" of publications, it can be argued that the g-index does not differ from the square root of the total number of citations in a bibliometrically meaningful way when the entire publication list is considered. The R-index also has a tendency to follow total impact, leaving only the A-index as a true measure of specific impact. The main difference between the g-index and the h-index is that the former penalizes consistency of impact whereas the latter rewards such consistency. It is concluded that the h-index is a better bibliometric tool than is the g-index, and that the square root of the total number of citations is a convenient measure of a researcher's overall impact.

Footnote

Vgl.: Visscher, A. De: Response to "remarks on the paper by a. De Visscher, 'what does the g-index really measure?' ". In: Journal of the American Society for Information Science and Technology. 62(2013) no.9, S.1960-1962.

Object

g-index

0.035693035 = product of:
  0.08923259 = sum of:
    0.054337036 = weight(_text_:index in 116) [ClassicSimilarity], result of:
      0.054337036 = score(doc=116,freq=2.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.24139762 = fieldWeight in 116, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0390625 = fieldNorm(doc=116)
    0.03489555 = weight(_text_:22 in 116) [ClassicSimilarity], result of:
      0.03489555 = score(doc=116,freq=2.0), product of:
        0.18038483 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.051511593 = queryNorm
        0.19345059 = fieldWeight in 116, 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=116)
  0.4 = coord(2/5)

Abstract

The origin of the abridged edition of the Dewey system goes back to 1894 when an outline of 192 pages based on the full 5th Edition (1894) was issued for small public and school libraries of North America. New editions have appeared regularly following closely the publication of new full editions. An abridged version, which is always in one volume, comprises an introduction, schedules, four tables (namely 1, 2, 3 and 4) only, and the relative index and other minor features of the full edition, and has shorter numbers. Abridged 15 is a logical abridgement of the DDC23 (2011) and is a product of a new approach to development of an abridged edition of the DDC. Its content has been derived from the DDC database applying a set of rules to extract the edition using the new (2010) version of the editorial support system. The revision process has been informed by interaction with an always widening and diversified Dewey community at home and abroad. It aims to improve the currency of the schedules continuing to serve as shelving tool while recognizing its 'other' uses as a spinoff of its simplicity and inexpensiveness.

Date

3. 3.2016 18:59:22

0.035693035 = product of:
  0.08923259 = sum of:
    0.054337036 = weight(_text_:index in 160) [ClassicSimilarity], result of:
      0.054337036 = score(doc=160,freq=2.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.24139762 = fieldWeight in 160, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0390625 = fieldNorm(doc=160)
    0.03489555 = weight(_text_:22 in 160) [ClassicSimilarity], result of:
      0.03489555 = score(doc=160,freq=2.0), product of:
        0.18038483 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.051511593 = queryNorm
        0.19345059 = fieldWeight in 160, 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=160)
  0.4 = coord(2/5)

Abstract

Kurz nach 11 Uhr erscheint ein seltsamer Mensch am InfoDesk der Universitätsbibliothek und spricht die diensthabende Bibliothekarin an: "Frosch!". Mh, was meint der? Sonst sagt er nichts. Will er sich vorstellen? Herr Frosch? Wurde er im Eingangsbereich von einem Frosch erschreckt, der sich zufällig dorthin verirrte? Sucht er Literatur zu Fröschen? Märchen, mit dem Froschkönig? Will er Froschschenkel zum Mittagessen zubereiten? Ein Erstsemester, der in Biologie sich mit dem Tier befasst? Frosch als Fresser oder als gefressen werden? Ist das etwa der Autor Karl Frosch oder sucht er Literatur von diesem? Ein der Sprache nicht ganz mächtiger Ausländer? Ein Verrückter? Mh, Alter, Geschlecht, Kleidung, Sprache, Gestik - all dies wird schnell durchgeprüft. Ganz so kurz, kann man doch eine Dipl.-Bibl. nicht so einfach ansprechen. Unverschämt! ... Ungewöhnlich? Keineswegs, ist dies doch unsere normale Art, sich mit Suchmaschinen und OPACs zu unterhalten. Ebenso wenig wie eine Bibliothekarin hier eine zufriedenstellende Antwort bieten kann, weiß auch keine Suchmaschine, was das Anliegen dieser Person ist. Weit schneller als die Bibliothekarin kann sie aber in ihrem Index das Suchwort aufspüren und eine Treffermenge vermelden. Der Schlitz der Suchmaschine hat im Gegensatz zum "Schlitz" der Bibliothek, dem InfoDesk, keine Augen und Ohren, hat kein stimulierendes Lächeln, die Frage weiter erläutern zu lassen.

Source

¬Die Kraft der digitalen Unordnung: 32. Arbeits- und Fortbildungstagung der ASpB e. V., Sektion 5 im Deutschen Bibliotheksverband, 22.-25. September 2009 in der Universität Karlsruhe. Hrsg: Jadwiga Warmbrunn u.a

0.035693035 = product of:
  0.08923259 = sum of:
    0.054337036 = weight(_text_:index in 5797) [ClassicSimilarity], result of:
      0.054337036 = score(doc=5797,freq=2.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.24139762 = fieldWeight in 5797, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5797)
    0.03489555 = weight(_text_:22 in 5797) [ClassicSimilarity], result of:
      0.03489555 = score(doc=5797,freq=2.0), product of:
        0.18038483 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.051511593 = queryNorm
        0.19345059 = fieldWeight in 5797, 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=5797)
  0.4 = coord(2/5)

Abstract

The article discusses various aspects of the Dewey Decimal Classification (DDC) system of classifying library books in 2013. Background is presented on some librarians' desire to stop using DDC and adopt a genre-based system of classification. It says librarians can use the DDC to deal with problems and issues related to library book classification. It highlights the benefits of using captions and relative index terms and semantic relationships in DDC.

Source

Knowledge quest. 42(2013) no.2, S.22-29

0.0347757 = product of:
  0.1738785 = sum of:
    0.1738785 = weight(_text_:index in 4453) [ClassicSimilarity], result of:
      0.1738785 = score(doc=4453,freq=8.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.7724724 = fieldWeight in 4453, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0625 = fieldNorm(doc=4453)
  0.2 = coord(1/5)

Abstract

Recently, it was shown that among existing theoretical models for the h-index, the Glänzel-Schubert model provides the best fit for a chosen example involving the research evaluation of universities. In this brief communication, we propose a thermodynamic explanation for the success of the Glänzel-Schubert model of the h-index.

Object

h-index

0.0347757 = product of:
  0.1738785 = sum of:
    0.1738785 = weight(_text_:index in 778) [ClassicSimilarity], result of:
      0.1738785 = score(doc=778,freq=8.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.7724724 = fieldWeight in 778, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0625 = fieldNorm(doc=778)
  0.2 = coord(1/5)

Abstract

I propose the index $\hbar$ ("hbar"), defined as the number of papers of an individual that have citation count larger than or equal to the $\hbar$ of all coauthors of each paper, as a useful index to characterize the scientific output of a researcher that takes into account the effect of multiple authorship. The bar is higher for $\hbar.$

Object

h-index

0.0347757 = product of:
  0.1738785 = sum of:
    0.1738785 = weight(_text_:index in 1113) [ClassicSimilarity], result of:
      0.1738785 = score(doc=1113,freq=8.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.7724724 = fieldWeight in 1113, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0625 = fieldNorm(doc=1113)
  0.2 = coord(1/5)

Abstract

Using a very small sample of 8 data sets it was recently shown by De Visscher (2011) that the g-index is very close to the square root of the total number of citations. It was argued that there is no bibliometrically meaningful difference. Using another somewhat larger empirical sample of 26 data sets I show that the difference may be larger and I argue in favor of the g-index.

Object

g-index

0.0347757 = product of:
  0.1738785 = sum of:
    0.1738785 = weight(_text_:index in 3313) [ClassicSimilarity], result of:
      0.1738785 = score(doc=3313,freq=8.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.7724724 = fieldWeight in 3313, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0625 = fieldNorm(doc=3313)
  0.2 = coord(1/5)

Abstract

This article proposes a parametric approach for facilitating inter-metric and inter-field comparisons of citation-based journal ranking metrics. The mechanism is simple to apply and adjusts for metric magnitude differentials and distributional asymmetries in the rank-score curves. The method is demonstrated using h-index, AWCR-index, g-index, and e-index data from journals in Accounting, Economics, and Finance.

0.034020368 = product of:
  0.17010184 = sum of:
    0.17010184 = weight(_text_:index in 463) [ClassicSimilarity], result of:
      0.17010184 = score(doc=463,freq=10.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.75569415 = fieldWeight in 463, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0546875 = fieldNorm(doc=463)
  0.2 = coord(1/5)

Abstract

The author presents a different view on properties of impact measures than given in the paper of De Visscher (2011). He argues that a good impact measure works better when citations are concentrated rather than spread out over articles. The author also presents theoretical evidence that the g-index and the R-index can be close to the square root of the total number of citations, whereas this is not the case for the A-index. Here the author confirms an assertion of De Visscher.

Object

g-index

0.034020368 = product of:
  0.17010184 = sum of:
    0.17010184 = weight(_text_:index in 2267) [ClassicSimilarity], result of:
      0.17010184 = score(doc=2267,freq=10.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.75569415 = fieldWeight in 2267, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2267)
  0.2 = coord(1/5)

Abstract

Various mathematical models have been proposed in the recent literature for estimating the h-index using measures such as number of articles (P) and citations received (C). These models have been previously empirically tested assuming a mathematical model and predetermining the models' parameter values at some fixed constant. The present study, from a statistical modeling viewpoint, investigates alternative distributions commonly used for this type of point data. The study shows that the typical assumptions for the parameters of the h-index mathematical models in such representations are not always realistic, with more suitable specifications being favorable. Prediction of the h-index is also demonstrated.

Object

h-index

0.03272563 = product of:
  0.16362813 = sum of:
    0.16362813 = weight(_text_:3a in 5820) [ClassicSimilarity], result of:
      0.16362813 = score(doc=5820,freq=2.0), product of:
        0.43671587 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.051511593 = queryNorm
        0.3746787 = fieldWeight in 5820, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.03125 = fieldNorm(doc=5820)
  0.2 = coord(1/5)

Content

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.

0.031943526 = product of:
  0.15971762 = sum of:
    0.15971762 = weight(_text_:index in 3336) [ClassicSimilarity], result of:
      0.15971762 = score(doc=3336,freq=12.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.7095612 = fieldWeight in 3336, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.046875 = fieldNorm(doc=3336)
  0.2 = coord(1/5)

Abstract

Adding or deleting items such as self-citations has an influence on the h-index of an author. This influence will be proved mathematically in this article. We hereby prove the experimental finding in E. Gianoli and M.A. Molina-Montenegro ([2009]) that the influence of adding or deleting self-citations on the h-index is greater for low values of the h-index. Why this is logical also is shown by a simple theoretical example. Adding or deleting sources such as adding or deleting minor contributions of an author also has an influence on the h-index of this author; this influence is modeled in this article. This model explains some practical examples found in X. Hu, R. Rousseau, and J. Chen (in press).

Object

h-index

0.031943526 = product of:
  0.15971762 = sum of:
    0.15971762 = weight(_text_:index in 1112) [ClassicSimilarity], result of:
      0.15971762 = score(doc=1112,freq=12.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.7095612 = fieldWeight in 1112, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.046875 = fieldNorm(doc=1112)
  0.2 = coord(1/5)

Abstract

In this article, we propose a measure to assess scientific impact that discounts self-citations and does not require any prior knowledge of their distribution among publications. This index can be applied to both researchers and journals. In particular, we show that it fills the gap of the h-index and similar measures that do not take into account the effect of self-citations for authors or journals impact evaluation. We provide 2 real-world examples: First, we evaluate the research impact of the most productive scholars in computer science (according to DBLP Computer Science Bibliography, Universität Trier, Trier, Germany); then we revisit the impact of the journals ranked in the Computer Science Applications section of the SCImago Journal & Country Rank ranking service (Consejo Superior de Investigaciones Científicas, University of Granada, Extremadura, Madrid, Spain). We observe how self-citations, in many cases, affect the rankings obtained according to different measures (including h-index and ch-index), and show how the proposed measure mitigates this effect.

Object

h-index

0.031943526 = product of:
  0.15971762 = sum of:
    0.15971762 = weight(_text_:index in 2344) [ClassicSimilarity], result of:
      0.15971762 = score(doc=2344,freq=12.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.7095612 = fieldWeight in 2344, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.046875 = fieldNorm(doc=2344)
  0.2 = coord(1/5)

Abstract

This study employs a panel threshold regression model to test whether the patent h-index has a threshold effect on the relationship between patent citations and market value in the pharmaceutical industry. It aims to bridge the gap in extant research on this topic. This study demonstrates that the patent h-index has a triple threshold effect on the relationship between patent citations and market value. When the patent h-index is less than or equal to the lowest threshold, 4, there is a positive relationship between patent citations and market value. This study indicates that the first regime (where the patent h-index is less than or equal to 4) is optimal, because this is where the extent of the positive relationship between patent citations and market value is the greatest.

Object

h-index

0.030737672 = product of:
  0.15368836 = sum of:
    0.15368836 = weight(_text_:index in 49) [ClassicSimilarity], result of:
      0.15368836 = score(doc=49,freq=4.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.6827756 = fieldWeight in 49, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.078125 = fieldNorm(doc=49)
  0.2 = coord(1/5)

Object

h-index

0.030737672 = product of:
  0.15368836 = sum of:
    0.15368836 = weight(_text_:index in 1508) [ClassicSimilarity], result of:
      0.15368836 = score(doc=1508,freq=4.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.6827756 = fieldWeight in 1508, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.078125 = fieldNorm(doc=1508)
  0.2 = coord(1/5)

Abstract

It is shown that a normalized version of the g-index is a good normalized impact and concentration measure. A proposal for such a measure by Bartolucci is improved.

Object

g-index

0.030737672 = product of:
  0.15368836 = sum of:
    0.15368836 = weight(_text_:index in 3165) [ClassicSimilarity], result of:
      0.15368836 = score(doc=3165,freq=16.0), product of:
        0.2250935 = queryWeight, product of:
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.051511593 = queryNorm
        0.6827756 = fieldWeight in 3165, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          4.369764 = idf(docFreq=1520, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3165)
  0.2 = coord(1/5)

Abstract

Purpose The purpose of this paper is to show how bibliometrics would benefit from a stronger programme of construct validity. Design/methodology/approach The value of the construct validity concept is demonstrated by applying this approach to the evaluation of the h-index, a widely used metric. Findings The paper demonstrates that the h-index comprehensively fails any test of construct validity. In simple terms, the metric does not measure what it purports to measure. This conclusion suggests that the current popularity of the h-index as a topic for bibliometric research represents wasted effort, which might have been avoided if researchers had adopted the approach suggested in this paper. Research limitations/implications This study is based on the analysis of a single bibliometric concept. Practical implications The conclusion that the h-index fails any test in terms of construct validity implies that the widespread use of this metric within the higher education sector as a management tool represents poor practice, and almost certainly results in the misallocation of resources. Social implications This paper suggests that the current enthusiasm for the h-index within the higher education sector is misplaced. The implication is that universities, grant funding bodies and faculty administrators should abandon the use of the h-index as a management tool. Such a change would have a significant effect on current hiring, promotion and tenure practices within the sector, as well as current attitudes towards the measurement of academic performance. Originality/value The originality of the paper lies in the systematic application of the concept of construct validity to bibliometric enquiry.

Object

h-index