Improvement And Implementation Of A Number Of Algorithms In Concept Analysis,

Formal concept analysis is a lattice-based tool for data analysis, it can be considered as an algorithm of data-mining and has been used in data analysis and knowledge processing. Concept lattice is the most important data type in formal concept analysis, it represents the integration of intents and extents in concepts and it is very suit for the extraction of rules. Concept lattice is a formalized tool for data analysis and had been used in many different disciplines.The generation of concept lattice plays an important role in the applications of concept lattice. So we should pay more attention to the algorithm for building concept lattice. There are many different algorithms for building concept lattice, and these algorithms can be divided into two main categories which we called batch construction and incremental construction. The batch algorithms are used for building concept lattice whose formal context had been given and the algorithms of incremental construction are more convenient than batch algorithms with dynamic data.This thesis is focus on the batch algorithms. The following is our main research works:1. Introduce some basic algorithm for building concept lattice. Thenwe carried out the algorithm 3, and got the Hasse diagram of this algorithm.2. Compare the feature of some batch algorithms, we introduced and carried out a new batch algorithm. Then based on the concept lattice, we constructed a new algorithm for drawing the Hasse diagram.