A knowledge acquisition method based on concept lattice and inclusion degree for ordered information systems

In some information system with order features, when users consider “greater than” or “less than” relations to a certain degree rather than in the full sense, using traditional methods may face great limitations. In light of natural connections among concept lattice, inclusion degree, order relations, and the feasibility of mutual integration among the three (concept lattice is essentially a type of data analysis tool using binary relations as research objects, while inclusion degree is a type of powerful tool for measuring uncertain order relations), the paper attempts to analyze uncertain order relations quantitatively within the framework of integration theory of concept lattice and inclusion degree. By which, the research scope of order relations undergoes an expansion-to-contraction process. Namely, certain order relations are first expanded to fuzzy or uncertain relations, and then the fuzzy or uncertain relations are allowed to contract to a degree of certainty by setting threshold parameters. Clearly, by properly widening the research scope of order relations, the model not only has good robustness and generalization ability, but also can meet actual needs flexibly. On this basis, solutions for algebraic structure, reduction, core, dependency, et al. are further studied deeply in ordered information systems. In short, the paper, as a meaningful try and exploration, is conducive to the integration of theories, and may offer some new and feasible ways for the study of order relations and ordered information systems.