N-ary Relations for Logical Analysis of Data and Knowledge

N-ary Relations for Logical Analysis of Data and Knowledge

Boris Kulik (Russian Academy of Science, Russia) and Alexander Fridman (Russian Academy of Science, Russia)
Release Date: November, 2017|Copyright: © 2018 |Pages: 297
ISBN13: 9781522527824|ISBN10: 1522527826|EISBN13: 9781522527831|DOI: 10.4018/978-1-5225-2782-4

Description

Mathematics has been used as a tool in logistical reasoning for centuries. Examining how specific mathematic structures can aid in data and knowledge management helps determine how to efficiently and effectively process more information in these fields.

N-ary Relations for Logical Analysis of Data and Knowledge is a critical scholarly reference source that provides a detailed study of the mathematical techniques currently involved in the progression of information technology fields. Featuring relevant topics that include algebraic sets, deductive analysis, defeasible reasoning, and probabilistic modeling, this publication is ideal for academicians, students, and researchers who are interested in staying apprised of the latest research in the information technology field.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Algebraic Sets
  • Artificial Intelligence Systems
  • Data Management
  • Deductive Analysis
  • Defeasible Reasoning
  • Logical Inference Systems
  • Probabilistic Logic
  • Probabilistic Modeling

Table of Contents and List of Contributors

Search this Book:
Reset