Content area
The immersion of voluminous collection of data is inevitable almost everywhere. The invention of mathematical models to analyse the patterns and trends of the data is an emerging necessity to extract and predict useful information in any Knowledge Discovery from Data (KDD) process. The Formal Concept Analysis (FCA) is an efficient mathematical model used in the process of KDD which is specially designed to portray the structure of the data in a context and depict the underlying patterns and hierarchies in it. Due to the huge increase in the application of FCA in various fields, the number of research and review articles on FCA has raised to a large extent. This review differs from the existing ones in presenting the comprehensive survey on the fundamentals of FCA in a compact and crisp manner to benefit the beginners and its focuses on the scalability issues in FCA. Further, we present the generic anatomy of FCA apart from its origin and growth at a primary level.
Details
Computer Oriented Programs;
Knowledge Management;
Electronic Learning;
Data Analysis;
Information Retrieval;
Influence of Technology;
Researchers;
Information Security;
Educational Technology;
Mathematical Models;
Engineering Education;
Periodicals;
College Science;
Discovery Processes;
Social Sciences;
Engineering Technology;
Computer Science;
Trend Analysis;
Knowledge Representation;
Information Technology