Compression N Order Operator Object-oriented (property) Based On Concept Lattice

Formal concept analysis(FCA) and rough set theory provide two methods for us to manage the uncertain data in the field of intelligent data processing research. They get the useful information via their own research methods and theories. As two powerful data analysis tools, they have been paid attention by many scholars and have been successfully used in granular computing, image processing, knowledge discovery, management science and other fields.However, with the coming of Big Data, it becomes more and more complicate to find the effective knowledge since the data become more complex. This is a new interesting field to be researched, and compression of concept lattices is one kind of efficient way to solve this problem. The paper discusses the compression of the property-oriented concept lattice and the object-oriented concept lattice.The main results are summarized as follows:1. We propose a definition of n order operator, study its properties, and compare them with□,◇operator.2. Start from formal context, we propose a concept lattice compression method based on n order operator. Through producing n order object-oriented (attribute-oriented) concept and adjusting the size of the n, we get the dynamic compression of the property-oriented concept lattice and the object-oriented concept lattice.