Coverage Density Based Approach for Concept Lattice Reduction
基于覆盖度函数的概念格约简

To address the lattice size exponential explosion problem in large scale data and rule mining, concept coverage density function and measurement model are introduced to reduce redundant concepts. The pruned lattice, named marked-concept lattice, has linear space complexity and can be obtained through direct or synchronous construction or node-extraction. Analysis and simulation tests show that this reduction model not only significantly reduces normal concept lattice size, but also significantly improves lattice building and rule mining efficiency. Furthermore, marked concept carries crucial information and physical meanings, thus can make benefits for Web service relationship mining.