Weighted Concept Lattice and Incremental Construction

Concept lattice is an efficient formal tool for data analysis and knowledge extraction. The presented researches presume that all the intensions of the concept lattice are equally important. However, the importance of the attributes consisting of the intension is often different in practice. In order to take advantage of concept lattice for analyzing data and knowledge extraction completely, we introduce the weight value into the intension of the concept lattice and present a new concept lattice, a weighted concept lattice (WCL), which develops the concept lattice structure. The lowest intension threshold is defined by the user. According to the threshold, we build a frequent weighted concept lattice (FWCL) and give one incremental construction algorithm and algorithm analysis for the FWCL. Finally, the example illustrates its efficiency and feasibility.