-
Egghe, L.; Rousseau, R.: Duality in information retrieval and the hypegeometric distribution (1997)
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- Abstract
- Asserts that duality is an important topic in informetrics, especially in connection with the classical informetric laws. Yet this concept is less studied in information retrieval. It deals with the unification or symmetry between queries and documents, search formulation versus indexing, and relevant versus retrieved documents. Elaborates these ideas and highlights the connection with the hypergeometric distribution
-
Egghe, L.: ¬A new short proof of Naranan's theorem, explaining Lotka's law and Zipf's law (2010)
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- Abstract
- Naranan's important theorem, published in Nature in 1970, states that if the number of journals grows exponentially and if the number of articles in each journal grows exponentially (at the same rate for each journal), then the system satisfies Lotka's law and a formula for the Lotka's exponent is given in function of the growth rates of the journals and the articles. This brief communication re-proves this result by showing that the system satisfies Zipf's law, which is equivalent with Lotka's law. The proof is short and algebraic and does not use infinitesimal arguments.
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.12, S.2581-2583
-
Egghe, L.; Rousseau, R.; Hooydonk, G. van: Methods for accrediting publications to authors or countries : consequences for evaluation studies (2000)
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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
-
Egghe, L.: ¬The power of power laws and an interpretation of Lotkaian informetric systems as self-similar fractals (2005)
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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
-
Egghe, L.: Type/Token-Taken informetrics (2003)
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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
-
Egghe, L.: Untangling Herdan's law and Heaps' law : mathematical and informetric arguments (2007)
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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
-
Egghe, L.; Rousseau, R.: Averaging and globalising quotients of informetric and scientometric data (1996)
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- Source
- Journal of information science. 22(1996) no.3, S.165-170
-
Egghe, L.; Rousseau, R.: Introduction to informetrics : quantitative methods in library, documentation and information science (1990)
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- COMPASS
- Information science / Statistical mathematics
- LCSH
- Information science / Statistical methods
- Subject
- Information science / Statistical mathematics
Information science / Statistical methods
-
Egghe, L.: Expansion of the field of informetrics : the second special issue (2006)
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- Source
- Information processing and management. 42(2006) no.6, S.1405-1407
-
Egghe, L.: Expansion of the field of informetrics : origins and consequences (2005)
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- Source
- Information processing and management. 41(2005) no.6, S.1311-1316
-
Egghe, L.: Special features of the author - publication relationship and a new explanation of Lotka's law based on convolution theory (1994)
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- Source
- Journal of the American Society for Information Science. 45(1994) no.6, S.422-427
-
Egghe, L.: Note on a possible decomposition of the h-Index (2013)
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- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.4, S.871
-
Egghe, L.: ¬The Hirsch index and related impact measures (2010)
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- Annual review of information science and technology. 44(2010) no.1, S.65-114
-
Egghe, L.: ¬A good normalized impact and concentration measure (2014)
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- Journal of the Association for Information Science and Technology. 65(2014) no.10, S.2052-2054
-
Egghe, L.: ¬The influence of transformations on the h-index and the g-index (2008)
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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
-
Egghe, L.; Guns, R.; Rousseau, R.: Thoughts on uncitedness : Nobel laureates and Fields medalists as case studies (2011)
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- Footnote
- Vgl.: Erratum. In: Journal of the American Society for Information Science and Technology. 63(2012) no.2, S.429.
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1637-1644
-
Egghe, L.: On the law of Zipf-Mandelbrot for multi-word phrases (1999)
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- Journal of the American Society for Information Science. 50(1999) no.3, S.233-241
-
Egghe, L.; Rousseau, R.: ¬The influence of publication delays on the observed aging distribution of scientific literature (2000)
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- Journal of the American Society for Information Science. 51(2000) no.2, S.158-165
-
Egghe, L.; Liang, L.; Rousseau, R.: ¬A relation between h-index and impact factor in the power-law model (2009)
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- Journal of the American Society for Information Science and Technology. 60(2009) no.11, S.2362-2365
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Egghe, L.: Dynamic h-index : the Hirsch index in function of time (2007)
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- Journal of the American Society for Information Science and Technology. 58(2007) no.3, S.452-454
