Search (11 results, page 1 of 1)

0.013975062 = product of:
  0.027950125 = sum of:
    0.027950125 = product of:
      0.05590025 = sum of:
        0.05590025 = weight(_text_:h in 147) [ClassicSimilarity], result of:
          0.05590025 = score(doc=147,freq=10.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.4910324 = fieldWeight in 147, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0625 = fieldNorm(doc=147)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

When there are a group of articles and the present time is fixed we can determine the unique number h being the number of articles that received h or more citations while the other articles received a number of citations which is not larger than h. In this article, the time dependence of the h-index is determined. This is important to describe the expected career evolution of a scientist's work or of a journal's production in a fixed year.

0.013975062 = product of:
  0.027950125 = sum of:
    0.027950125 = product of:
      0.05590025 = sum of:
        0.05590025 = weight(_text_:h in 695) [ClassicSimilarity], result of:
          0.05590025 = score(doc=695,freq=10.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.4910324 = fieldWeight in 695, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0625 = fieldNorm(doc=695)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

An h-type index is proposed which depends on the obtained citations of articles belonging to the h-core. This weighted h-index, denoted as hw, is presented in a continuous setting and in a discrete one. It is shown that in a continuous setting the new index enjoys many good properties. In the discrete setting some small deviations from the ideal may occur.

Object

h-index

0.013257908 = product of:
  0.026515815 = sum of:
    0.026515815 = product of:
      0.05303163 = sum of:
        0.05303163 = weight(_text_:h in 1878) [ClassicSimilarity], result of:
          0.05303163 = score(doc=1878,freq=16.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.4658342 = fieldWeight in 1878, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.046875 = fieldNorm(doc=1878)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In this article, for any group of authors, we define three different h-indices. First, there is the successive h-index h2 based on the ranked list of authors and their h-indices h1 as defined by Schubert (2007). Next, there is the h-index hP based on the ranked list of authors and their number of publications. Finally, there is the h-index hC based on the ranked list of authors and their number of citations. We present formulae for these three indices in Lotkaian informetrics from which it also follows that h2 < hp < hc. We give a concrete example of a group of 167 authors on the topic optical flow estimation. Besides these three h-indices, we also calculate the two-by-two Spearman rank correlation coefficient and prove that these rankings are significantly related.

Object

h-index

0.012352326 = product of:
  0.024704652 = sum of:
    0.024704652 = product of:
      0.049409304 = sum of:
        0.049409304 = weight(_text_:h in 2009) [ClassicSimilarity], result of:
          0.049409304 = score(doc=2009,freq=20.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.4340154 = fieldWeight in 2009, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2009)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The article studies the influence of the query formulation of a topic on its h-index. In order to generate pure random sets of documents, we used N-grams (N variable) to measure this influence: strings of zeros, truncated at the end. The used databases are WoS and Scopus. The formula h=T**1/alpha, proved in Egghe and Rousseau (2006) where T is the number of retrieved documents and is Lotka's exponent, is confirmed being a concavely increasing function of T. We also give a formula for the relation between h and N the length of the N-gram: h=D10**(-N/alpha) where D is a constant, a convexly decreasing function, which is found in our experiments. Nonlinear regression on h=T**1/alpha gives an estimation of , which can then be used to estimate the h-index of the entire database (Web of Science [WoS] and Scopus): h=S**1/alpha, , where S is the total number of documents in the database.

Object

h-index

0.01222818 = product of:
  0.02445636 = sum of:
    0.02445636 = product of:
      0.04891272 = sum of:
        0.04891272 = weight(_text_:h in 1881) [ClassicSimilarity], result of:
          0.04891272 = score(doc=1881,freq=10.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.42965335 = fieldWeight in 1881, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1881)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In a previous article, we introduced a general transformation on sources and one on items in an arbitrary information production process (IPP). In this article, we investigate the influence of these transformations on the h-index and on the g-index. General formulae that describe this influence are presented. These are applied to the case that the size-frequency function is Lotkaian (i.e., is a decreasing power function). We further show that the h-index of the transformed IPP belongs to the interval bounded by the two transformations of the h-index of the original IPP, and we also show that this property is not true for the g-index.

Object

h-index

0.011481686 = product of:
  0.022963371 = sum of:
    0.022963371 = product of:
      0.045926742 = sum of:
        0.045926742 = weight(_text_:h in 2004) [ClassicSimilarity], result of:
          0.045926742 = score(doc=2004,freq=12.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.40342426 = fieldWeight in 2004, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.046875 = fieldNorm(doc=2004)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This article studies the h-index (Hirsch index) and the g-index of authors, in case one counts authorship of the cited articles in a fractional way. There are two ways to do this: One counts the citations to these papers in a fractional way or one counts the ranks of the papers in a fractional way as credit for an author. In both cases, we define the fractional h- and g-indexes, and we present inequalities (both upper and lower bounds) between these fractional h- and g-indexes and their corresponding unweighted values (also involving, of course, the coauthorship distribution). Wherever applicable, examples and counterexamples are provided. In a concrete example (the publication citation list of the present author), we make explicit calculations of these fractional h- and g-indexes and show that they are not very different from the unweighted ones.

Object

h-index

0.011048257 = product of:
  0.022096515 = sum of:
    0.022096515 = product of:
      0.04419303 = sum of:
        0.04419303 = weight(_text_:h in 4217) [ClassicSimilarity], result of:
          0.04419303 = score(doc=4217,freq=16.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.3881952 = fieldWeight in 4217, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4217)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This paper studies mathematical properties of h-index sequences as developed by Liang [Liang, L. (2006). h-Index sequence and h-index matrix: Constructions and applications. Scientometrics, 69(1), 153-159]. For practical reasons, Liming studies such sequences where the time goes backwards while it is more logical to use the time going forward (real career periods). Both type of h-index sequences are studied here and their interrelations are revealed. We show cases where these sequences are convex, linear and concave. We also show that, when one of the sequences is convex then the other one is concave, showing that the reverse-time sequence, in general, cannot be used to derive similar properties of the (difficult to obtain) forward time sequence. We show that both sequences are the same if and only if the author produces the same number of papers per year. If the author produces an increasing number of papers per year, then Liang's h-sequences are above the "normal" ones. All these results are also valid for g- and R-sequences. The results are confirmed by the h-, g- and R-sequences (forward and reverse time) of the author.

Object

h-index

0.009312361 = product of:
  0.018624721 = sum of:
    0.018624721 = product of:
      0.037249442 = sum of:
        0.037249442 = weight(_text_:22 in 2558) [ClassicSimilarity], result of:
          0.037249442 = score(doc=2558,freq=2.0), product of:
            0.16046064 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045821942 = queryNorm
            0.23214069 = fieldWeight in 2558, 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=2558)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

14. 8.2004 19:17:22

0.008838605 = product of:
  0.01767721 = sum of:
    0.01767721 = product of:
      0.03535442 = sum of:
        0.03535442 = weight(_text_:h in 6759) [ClassicSimilarity], result of:
          0.03535442 = score(doc=6759,freq=4.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.31055614 = fieldWeight in 6759, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0625 = fieldNorm(doc=6759)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Object

h-index

0.0077337795 = product of:
  0.015467559 = sum of:
    0.015467559 = product of:
      0.030935118 = sum of:
        0.030935118 = weight(_text_:h in 3124) [ClassicSimilarity], result of:
          0.030935118 = score(doc=3124,freq=4.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.27173662 = fieldWeight in 3124, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3124)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

We present a rationale for the Hirsch-index rank-order distribution and prove that it is a power law (hence a straight line in the log-log scale). This is confirmed by experimental data of Pyykkö and by data produced in this article on 206 mathematics journals. This distribution is of a completely different nature than the impact factor (IF) rank-order distribution which (as proved in a previous article) is S-shaped. This is also confirmed by our example. Only in the log-log scale of the h-index distribution do we notice a concave deviation of the straight line for higher ranks. This phenomenon is discussed.

Object

h-index

0.0031249188 = product of:
  0.0062498376 = sum of:
    0.0062498376 = product of:
      0.012499675 = sum of:
        0.012499675 = weight(_text_:h in 81) [ClassicSimilarity], result of:
          0.012499675 = score(doc=81,freq=2.0), product of:
            0.113842286 = queryWeight, product of:
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.045821942 = queryNorm
            0.10979818 = fieldWeight in 81, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4844491 = idf(docFreq=10020, maxDocs=44218)
              0.03125 = fieldNorm(doc=81)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Source

Information - Wissenschaft und Praxis. 57(2006) H.8, S.427-432