Book
Fitness of Information: Quantitative Assessments of Critical Evidence
01 Jan 2014
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Organized for readers to follow along easily, The Fitness of Information: Quantitative Assessments of Critical Evidence provides a structured outline of the key challenges in assessing crucial information in a complex adaptive system. Illustrating a variety of computational and explanatory challenges, the book demonstrates principles and practical implications of exploring and assessing the fitness of information in an extensible framework of adaptive landscapes.
The book’s first three chapters introduce fundamental principles and practical examples in connection to the nature of aesthetics, mental models, and the subjectivity of evidence. In particular, the underlying question is how these issues can be addressed quantitatively, not only computationally but also explanatorily. The next chapter illustrates how one can reduce the level of complexity in understanding the structure and dynamics of scientific knowledge through the design and use of the CiteSpace system for visualizing and analyzing emerging trends in scientific literature. The following two chapters explain the concepts of structural variation and the fitness of information in a framework that builds on the idea of fitness landscape originally introduced to study population evolution. The final chapter presents a dual-map overlay technique and demonstrates how it supports a variety of analytic tasks for a new type of portfolio analysis.
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Details
- Title
- Fitness of Information: Quantitative Assessments of Critical Evidence
- Creators
- C Chen - Drexel University, Information Science
- Series
- Wiley Series in Probability and Statistics
- Publisher
- Wiley; OXFORD
- Number of pages
- 256
- Resource Type
- Book
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000449912300009
- Scopus ID
- 2-s2.0-84926116572
- Other Identifier
- 9781118128336; 1118128338; 9781118594100; 111859410X; 991019333215504721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Social Sciences, Mathematical Methods
- Statistics & Probability