Search (26 results, page 1 of 2)

  • × author_ss:"Egghe, L."
  • × theme_ss:"Informetrie"
  • × year_i:[2000 TO 2010}
  1. Egghe, L.; Ravichandra Rao, I.K.: ¬The influence of the broadness of a query of a topic on its h-index : models and examples of the h-index of n-grams (2008) 0.00 
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    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.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.10, S.1688-1693
  2. Egghe, L.: Type/Token-Taken informetrics (2003) 0.00 
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    Abstract
    Type/Token-Taken informetrics is a new part of informetrics that studies the use of items rather than the items itself. Here, items are the objects that are produced by the sources (e.g., journals producing articles, authors producing papers, etc.). In linguistics a source is also called a type (e.g., a word), and an item a token (e.g., the use of words in texts). In informetrics, types that occur often, for example, in a database will also be requested often, for example, in information retrieval. The relative use of these occurrences will be higher than their relative occurrences itself; hence, the name Type/ Token-Taken informetrics. This article studies the frequency distribution of Type/Token-Taken informetrics, starting from the one of Type/Token informetrics (i.e., source-item relationships). We are also studying the average number my* of item uses in Type/Token-Taken informetrics and compare this with the classical average number my in Type/Token informetrics. We show that my* >= my always, and that my* is an increasing function of my. A method is presented to actually calculate my* from my, and a given a, which is the exponent in Lotka's frequency distribution of Type/Token informetrics. We leave open the problem of developing non-Lotkaian Type/TokenTaken informetrics.
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.7, S.603-610
  3. Egghe, L.: Untangling Herdan's law and Heaps' law : mathematical and informetric arguments (2007) 0.00 
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    Abstract
    Herdan's law in linguistics and Heaps' law in information retrieval are different formulations of the same phenomenon. Stated briefly and in linguistic terms they state that vocabularies' sizes are concave increasing power laws of texts' sizes. This study investigates these laws from a purely mathematical and informetric point of view. A general informetric argument shows that the problem of proving these laws is, in fact, ill-posed. Using the more general terminology of sources and items, the author shows by presenting exact formulas from Lotkaian informetrics that the total number T of sources is not only a function of the total number A of items, but is also a function of several parameters (e.g., the parameters occurring in Lotka's law). Consequently, it is shown that a fixed T(or A) value can lead to different possible A (respectively, T) values. Limiting the T(A)-variability to increasing samples (e.g., in a text as done in linguistics) the author then shows, in a purely mathematical way, that for large sample sizes T~ A**phi, where phi is a constant, phi < 1 but close to 1, hence roughly, Heaps' or Herdan's law can be proved without using any linguistic or informetric argument. The author also shows that for smaller samples, a is not a constant but essentially decreases as confirmed by practical examples. Finally, an exact informetric argument on random sampling in the items shows that, in most cases, T= T(A) is a concavely increasing function, in accordance with practical examples.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.5, S.702-709
  4. Egghe, L.: Expansion of the field of informetrics : the second special issue (2006) 0.00 
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    Source
    Information processing and management. 42(2006) no.6, S.1405-1407
  5. Egghe, L.: Expansion of the field of informetrics : origins and consequences (2005) 0.00 
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    Source
    Information processing and management. 41(2005) no.6, S.1311-1316
  6. Egghe, L.: ¬The influence of transformations on the h-index and the g-index (2008) 0.00 
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    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.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.8, S.1304-1312
  7. Egghe, L.; Rousseau, R.; Hooydonk, G. van: Methods for accrediting publications to authors or countries : consequences for evaluation studies (2000) 0.00 
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    Abstract
    One aim of science evaluation studies is to determine quantitatively the contribution of different players (authors, departments, countries) to the whole system. This information is then used to study the evolution of the system, for instance to gauge the results of special national or international programs. Taking articles as our basic data, we want to determine the exact relative contribution of each coauthor or each country. These numbers are brought together to obtain country scores, or department scores, etc. It turns out, as we will show in this article, that different scoring methods can yield totally different rankings. Conseqeuntly, a ranking between countries, universities, research groups or authors, based on one particular accrediting methods does not contain an absolute truth about their relative importance
    Source
    Journal of the American Society for Information Science. 51(2000) no.2, S.145-157
  8. Egghe, L.; Rousseau, R.: ¬The influence of publication delays on the observed aging distribution of scientific literature (2000) 0.00 
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    Source
    Journal of the American Society for Information Science. 51(2000) no.2, S.158-165
  9. Egghe, L.; Liang, L.; Rousseau, R.: ¬A relation between h-index and impact factor in the power-law model (2009) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.11, S.2362-2365
  10. Egghe, L.: Dynamic h-index : the Hirsch index in function of time (2007) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.3, S.452-454
  11. Egghe, L.: ¬The power of power laws and an interpretation of Lotkaian informetric systems as self-similar fractals (2005) 0.00 
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    Abstract
    Power laws as defined in 1926 by A. Lotka are increasing in importance because they have been found valid in varied social networks including the Internet. In this article some unique properties of power laws are proven. They are shown to characterize functions with the scalefree property (also called seif-similarity property) as weIl as functions with the product property. Power laws have other desirable properties that are not shared by exponential laws, as we indicate in this paper. Specifically, Naranan (1970) proves the validity of Lotka's law based on the exponential growth of articles in journals and of the number of journals. His argument is reproduced here and a discrete-time argument is also given, yielding the same law as that of Lotka. This argument makes it possible to interpret the information production process as a seif-similar fractal and show the relation between Lotka's exponent and the (seif-similar) fractal dimension of the system. Lotkaian informetric systems are seif-similar fractals, a fact revealed by Mandelbrot (1977) in relation to nature, but is also true for random texts, which exemplify a very special type of informetric system.
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.669-675
  12. Egghe, L.: Sampling and concentration values of incomplete bibliographies (2002) 0.00 
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    Journal of the American Society for Information Science and technology. 53(2002) no.4, S.271-281
  13. Egghe, L.; Rousseau, R.; Rousseau, S.: TOP-curves (2007) 0.00 
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    Journal of the American Society for Information Science and Technology. 58(2007) no.6, S.777-785
  14. Egghe, L.; Liang, L.; Rousseau, R.: Fundamental properties of rhythm sequences (2008) 0.00 
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    Journal of the American Society for Information Science and Technology. 59(2008) no.9, S.1469-1478
  15. Egghe, L.: ¬A rationale for the Hirsch-index rank-order distribution and a comparison with the impact factor rank-order distribution (2009) 0.00 
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    Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.2142-2144
  16. Egghe, L.; Rousseau, R.: Aging, obsolescence, impact, growth, and utilization : definitions and relations (2000) 0.00 
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    Journal of the American Society for Information Science. 51(2000) no.11, S.1004-1017
  17. Egghe, L.: ¬A noninformetric analysis of the relationship between citation age and journal productivity (2001) 0.00 
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    Journal of the American Society for Information Science and technology. 52(2001) no.5, S.371-377
  18. Egghe, L.; Ravichandra Rao, I.K.: Duality revisited : construction of fractional frequency distributions based on two dual Lotka laws (2002) 0.00 
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    Journal of the American Society for Information Science and technology. 53(2002) no.10, S.789-801
  19. Egghe, L.: Relations between the continuous and the discrete Lotka power function (2005) 0.00 
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    Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.664-668
  20. Egghe, L.: Zipfian and Lotkaian continuous concentration theory (2005) 0.00 
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  0.071428575 = coord(1/14)
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.9, S.935-945

Authors