Next Article in Journal / Special Issue
Information as a Manifestation of Development
Previous Article in Journal / Special Issue
Empirical Information Metrics for Prediction Power and Experiment Planning
Open AccessArticle

On Quantifying Semantic Information

Department of Philosophy, East Wing, Old Quad, The University of Melbourne, Victoria 3010, Australia
Information 2011, 2(1), 61-101;
Received: 17 November 2010 / Revised: 10 January 2011 / Accepted: 17 January 2011 / Published: 18 January 2011
(This article belongs to the Special Issue What Is Information?)
The purpose of this paper is to look at some existing methods of semantic information quantification and suggest some alternatives. It begins with an outline of Bar-Hillel and Carnap’s theory of semantic information before going on to look at Floridi’s theory of strongly semantic information. The latter then serves to initiate an in-depth investigation into the idea of utilising the notion of truthlikeness to quantify semantic information. Firstly, a couple of approaches to measure truthlikeness are drawn from the literature and explored, with a focus on their applicability to semantic information quantification. Secondly, a similar but new approach to measure truthlikeness/information is presented and some supplementary points are made. View Full-Text
Keywords: information quantification; semantic information; Bar-Hillel; Carnap; Floridi; Truthlikeness information quantification; semantic information; Bar-Hillel; Carnap; Floridi; Truthlikeness
MDPI and ACS Style

D’Alfonso, S. On Quantifying Semantic Information. Information 2011, 2, 61-101.

Show more citation formats Show less citations formats

Article Access Map

Only visits after 24 November 2015 are recorded.
Information, EISSN 2078-2489, Published by MDPI AG
Back to TopTop