Production and use of information. Characterization of informetric distributions using effort function and density function - Exponential informetric process

Lafouge T; Prime-Claverie C

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Production and use of information. Characterization of informetric distributions using effort function and density function - Exponential informetric process

机译：生产和使用信息。使用力函数和密度函数表征不对称分布-指数不对称过程

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Statistical regularities observed in the production or use of information have been studied for a long time. In this article we define an exponential informetric process to formalize these stochastic process. It is defined by combining an effort function with a density function. Without using the powerful results of Price on the cumulative advantages process this characterization clarifies the principle of least effort. Some links between statistical theory of information and some informetric distributions are enhanced. (c) 2005 Elsevier Ltd. All rights reserved.

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《Information Processing & Management》 |2005年第6期|p. 1387-1394|共8页
作者
Lafouge T; Prime-Claverie C;
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作者单位

Univ Lyon 1, Lab Ursidoc, F-69622 Villeurbanne, France;

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原文格式 PDF
正文语种 eng
中图分类图书馆学、图书馆事业;
关键词
effort function; exponential process; entropy; ENTROPY;

机译：功函数指数过程熵熵;

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1. An interpretation of the effort function through the mathematical formalism of Exponential Informetric Process [J] . Lafouge T, Smolczewska A Information Processing & Management . 2006,第6期

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2. The source-effort coverage of an exponential informetric process [J] . Lafouge Thierry, Agouzal Abdelatif Journal of informetrics . 2015,第1期

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3. A continuous description of discrete data points in informetrics Using spline functions [J] . Yuxian Liu, Ronald Rousseau Aslib Proceedings . 2012,第2期

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4. Value distributions of exponential sums from perfect nonlinear functions [C] . Hai Xin, Li Chao 2010 International Conference on Computer Application and System Modeling . 2010

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7. An interpretation of the effort function through the mathematical formalism of Exponential Informetric Process [O] . Thierry Lafouge, Agnieszka Smolczewka 2015

机译：通过指数不对称过程的数学形式来解释努力函数
8. An Upper Bound on the Probability Density Function in Terms of Fisher Information. A Bound to the Density Function [R] . Klonias, V. K. 1981

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Production and use of information. Characterization of informetric distributions using effort function and density function - Exponential informetric process

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