An Information Fusion Technology And Cognitive System In Triadic Formal Concept Analysis

With the advent of the era of big data, it has become a hot topic to deal with large-scale, complex and synthetic data and extract interesting information from it.It is effective to apply concept lattice theory in data analysis and knowledge acquisition. However, as the types of data and the relationship between each other are more and more complex, it may have some shortcomings. So it is necessary for us to bring some new theories and methods so as to extend the application of concept lattice theory in data mining. Based the formal concept analysis, the triadic formal concept analysis increase the condition sets, then the concept lattice can be applied widely in processing the triadic relations.The main innovations are as follows:(1) The notion of a projected context is proposed to explore a novel algorithm of computing triadic concepts of a triadic context, and a triadic decision context is defined by combining triadic contexts. Then a rule acquisition method is presented for triadic decision contexts. It can be considered as an information fusion technology for decision-making analysis of multi-source data if the data under each condition is viewed as a single source data. Moreover, a knowledge reduction framework is established to simplify knowledge discovery. Finally, discernibility matrix and Boolean function are constructed to compute all reducts, which is beneficial to the acquisition of compact rules from a triadic decision context.(2) The following mainly focus on cognitive system model in the framework of triadic formal concept analysis. More precisely, the notions of sufficient information granule, necessary information granule, and sufficient and necessary information granule are necessary. Also, methods of transforming arbitrary information granule into sufficient, necessary, and sufficient and necessary information granule are presented under the background of fixing the third dimension.