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Enhancement of Knowledge Resources and Discovery by Computation of Content Factors

Authors:
Claus-Peter Rückemann

Keywords: Data-centric Knowledge Processing; Content Factor (CONTFACT) method; Data Rhythm Analysis; Universal Decimal Classification; Advanced Computing.

Abstract:
This paper presents a methodology for data description and analysis, the Content Factor (CONTFACT). The Content Factor method can be applied to arbitrary data and content and it can be adopted for many purposes. Normed factors and variants can also support data analysis and knowledge discovery. This paper presents the algorithm, introduces into the norming of Content Factors, and discusses examples and a practical case study and implementation based on long-term knowledge resources, which are continuously in development. The methodology is used for advanced processing and also enables methods like data rhythm analysis and characterisation. It can be integrated with complementary methodology, e.g., classification and allows the application of advanced computing methods. The goal of this research is to create a general and flexible methodology for data description and analysis that can be used with huge structured and even unstructured data resources, allows an automation, and can therefore also be used for long-term multi-disciplinary knowledge.

Pages: 24 to 31

Copyright: Copyright (c) IARIA, 2016

Publication date: May 22, 2016

Published in: conference

ISSN: 2308-3484

ISBN: 978-1-61208-478-7

Location: Valencia, Spain

Dates: from May 22, 2016 to May 26, 2016