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  • × author_ss:"Egghe, L."
  1. Egghe, L.: Existence theorem of the quadruple (P, R, F, M) : precision, recall, fallout and miss (2007) 0.06
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    Abstract
    In an earlier paper [Egghe, L. (2004). A universal method of information retrieval evaluation: the "missing" link M and the universal IR surface. Information Processing and Management, 40, 21-30] we showed that, given an IR system, and if P denotes precision, R recall, F fallout and M miss (re-introduced in the paper mentioned above), we have the following relationship between P, R, F and M: P/(1-P)*(1-R)/R*F/(1-F)*(1-M)/M = 1. In this paper we prove the (more difficult) converse: given any four rational numbers in the interval ]0, 1[ satisfying the above equation, then there exists an IR system such that these four numbers (in any order) are the precision, recall, fallout and miss of this IR system. As a consequence we show that any three rational numbers in ]0, 1[ represent any three measures taken from precision, recall, fallout and miss of a certain IR system. We also show that this result is also true for two numbers instead of three.
    Source
    Information processing and management. 43(2007) no.1, S.265-272
  2. Egghe, L.: ¬A universal method of information retrieval evaluation : the "missing" link M and the universal IR surface (2004) 0.04
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    Date
    14. 8.2004 19:17:22
    Source
    Information processing and management. 40(2004) no.1, S.21-30
  3. Egghe, L.: Expansion of the field of informetrics : the second special issue (2006) 0.03
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    Source
    Information processing and management. 42(2006) no.6, S.1405-1407
  4. Egghe, L.: Expansion of the field of informetrics : origins and consequences (2005) 0.03
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    Source
    Information processing and management. 41(2005) no.6, S.1311-1316
  5. Egghe, L.: ¬The amount of actions needed for shelving and reshelving (1996) 0.02
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    Source
    Library management. 17(1996) no.1, S.18-24
  6. Egghe, L.; Rousseau, R.: ¬A theoretical study of recall and precision using a topological approach to information retrieval (1998) 0.02
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    Source
    Information processing and management. 34(1998) nos.2/3, S.191-218
  7. Egghe, L.; Rousseau, R.: ¬An h-index weighted by citation impact (2008) 0.02
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    Source
    Information processing and management. 44(2008) no.2, S.770-780
  8. Egghe, L.: Vector retrieval, fuzzy retrieval and the universal fuzzy IR surface for IR evaluation (2004) 0.02
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    Source
    Information processing and management. 40(2004) no.4, S.603-618
  9. Egghe, L.; Guns, R.; Rousseau, R.; Leuven, K.U.: Erratum (2012) 0.01
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    Date
    14. 2.2012 12:53:22
  10. Egghe, L.: ¬The measures precision, recall, fallout and miss as a function of the number of retrieved documents and their mutual interrelations (2008) 0.01
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    Source
    Information processing and management. 44(2008) no.2, S.856-876
  11. Egghe, L.: Mathematical study of h-index sequences (2009) 0.01
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    Source
    Information processing and management. 45(2009) no.2, S.288-297
  12. Egghe, L.: ¬A new short proof of Naranan's theorem, explaining Lotka's law and Zipf's law (2010) 0.01
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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.
  13. Egghe, L.: Properties of the n-overlap vector and n-overlap similarity theory (2006) 0.01
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    Abstract
    In the first part of this article the author defines the n-overlap vector whose coordinates consist of the fraction of the objects (e.g., books, N-grams, etc.) that belong to 1, 2, , n sets (more generally: families) (e.g., libraries, databases, etc.). With the aid of the Lorenz concentration theory, a theory of n-overlap similarity is conceived together with corresponding measures, such as the generalized Jaccard index (generalizing the well-known Jaccard index in case n 5 2). Next, the distributional form of the n-overlap vector is determined assuming certain distributions of the object's and of the set (family) sizes. In this section the decreasing power law and decreasing exponential distribution is explained for the n-overlap vector. Both item (token) n-overlap and source (type) n-overlap are studied. The n-overlap properties of objects indexed by a hierarchical system (e.g., books indexed by numbers from a UDC or Dewey system or by N-grams) are presented in the final section. The author shows how the results given in the previous section can be applied as well as how the Lorenz order of the n-overlap vector is respected by an increase or a decrease of the level of refinement in the hierarchical system (e.g., the value N in N-grams).
  14. Egghe, L.; Rousseau, R.; Hooydonk, G. van: Methods for accrediting publications to authors or countries : consequences for evaluation studies (2000) 0.01
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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
  15. Egghe, L.; Rousseau, R.: Averaging and globalising quotients of informetric and scientometric data (1996) 0.01
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    Source
    Journal of information science. 22(1996) no.3, S.165-170
  16. Egghe, L.: ¬The power of power laws and an interpretation of Lotkaian informetric systems as self-similar fractals (2005) 0.01
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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.
  17. Egghe, L.; Rousseau, R.: Topological aspects of information retrieval (1998) 0.01
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    Abstract
    Let (DS, DQ, sim) be a retrieval system consisting of a document space DS, a query space QS, and a function sim, expressing the similarity between a document and a query. Following D.M. Everett and S.C. Cater (1992), we introduce topologies on the document space. These topologies are generated by the similarity function sim and the query space QS. 3 topologies will be studied: the retrieval topology, the similarity topology and the (pseudo-)metric one. It is shown that the retrieval topology is the coarsest of the three, while the (pseudo-)metric is the strongest. These 3 topologies are generally different, reflecting distinct topological aspects of information retrieval. We present necessary and sufficient conditions for these topological aspects to be equal