A Quantitative Measure of Relevance Based on Kelly Gambling Theory

Autor:	Madsen, M.W., Colinet, M., Katrenko, S., Rendsvig, R.K.
Přispěvatelé:	Logic and Language (ILLC, FNWI/FGw), Faculteit der Geesteswetenschappen, ILLC (FGw)
Jazyk:	angličtina
Rok vydání:	2014
Předmět:	Quantitative measure Turing machine symbols.namesake Logarithm Relation (database) Random number generation symbols Gambling and information theory Relevance (information retrieval) Mathematical economics Measure (mathematics) Mathematics
Zdroj:	Pristine Perspectives on Logic, Language, and Computation ISBN: 9783662441152 ESSLLI Student Sessions Pristine Perspectives on Logic, Language, and Computation: ESSLLI 2012 and ESSLLI 2013 Student Sessions : selected papers, 124-141 STARTPAGE=124;ENDPAGE=141;TITLE=Pristine Perspectives on Logic, Language, and Computation
Popis:	This paper proposes a quantitative measure relevance which can quantify the difference between useful and useless facts. This measure evaluates sources of information according to how they affect the expected logarithmic utility of an agent. A number of reasons are given why this is often preferable to a naive value-of-information approach, and some properties and interpretations of the concept are presented, including a result about the relation between relevant information and Shannon information. Lastly, a number of illustrative examples of relevance measurements are discussed, including random number generation and job market signaling.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5d7352d60122a6a612c76f24452b6ed https://dare.uva.nl/personal/pure/en/publications/a-quantitative-measure-of-relevance-based-on-kelly-gambling-theory(645155f6-7691-4b6d-b281-ea1ade0885aa).html Zobrazit plný text záznamu