Learn More
The difficult job in association rules is to identify the frequent item sets immersed into the huge collection of data. The association rules can be discovered using Formal Concept Analysis (FCA). Several contexts often contain large number of rules and hence interesting rules are required to be determined. With this objective, this paper proposes a method(More)
Association rule mining is a standard technique used for finding the relationships among the itemsets in a database. The method of extracting the frequent itemsets from the database using existing algorithms has several disadvantages such as generation of large number of candidate itemsets, increase in computational time and database scan. With this aim,(More)
FCA is a mathematical framework that depicts knowledge derived from the data represented as formal context. The objective of this paper is to apply Formal Concept Analysis (FCA) to analyze the key performance areas (KPA) of faculty of an institute. While constructing the formal context we have considered the faculties as objects and their KPA as attributes.(More)
  • 1