The fuzzification of an information architecture for information integration

Abstract

We present a new information architecture based on one recently introduced to structure categorized but otherwise unstructured information. The new architecture is based on fuzzy set theory subset operations that define graph theory nodes. Two types of graph edges are defined such that a user interface based on this architecture can logically minimize the number of visible navigable edges and atoms of information. This minimization is understood to be one of the primary advantages of the architecture for human-computer interaction due to its mitigation of information overload. The advantages of hierarchical, organic, and sequential information architectures are fused by the new architecture and the dialectical method is also integrated—all of which are intended to enhance human-computer interaction. The new architecture can easily incorporate quantitative information, which can be converted into a fuzzy set theory representation with fuzzy clustering and other techniques. Moreover, traditionally qualitative information such as narrative, audio, and video, although naturally represented with crisp sets, can be represented with fuzzy sets. Therefore, the new architecture can fuse traditionally disparate types of information.