A novel word ranking method based on distorted entropy

Autor:	Hossein Mehri-Dehnavi, Hamzeh Agahi, Ali Mehri
Rok vydání:	2019
Předmět:	Statistics and Probability Charles darwin Computer science Tsallis entropy 0103 physical sciences Statistical inference 010306 general physics Condensed Matter Physics 01 natural sciences Algorithm Expected utility hypothesis 010305 fluids & plasmas Origin of species
Zdroj:	Physica A: Statistical Mechanics and its Applications. 521:484-492
ISSN:	0378-4371
Popis:	This paper proposes an application of distorted entropy as well-known tools for non-additive expected utility theory in word ranking. Our algorithms for two books “Statistical Inference” by Casella and Berger and “The Origin of Species” by Charles Darwin show that our method on the distorted entropy improves the corresponding ones in the literature.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5625562b4569de8433528e8ecfea9dd2 https://doi.org/10.1016/j.physa.2019.01.080 Zobrazit plný text záznamu Full Text from ScienceDirect