In this article I'll discuss knowledge componetization and knowledge perspectives for mixing and matching knowledge concept combinations. I'll also explore in some detail how we learn, how we process signals in our brains, and how hyperspatial semantic indexing can facilitate the process.

Semantic tagging lights the path
Not only can 2G-KM (Second Generation Knowledge Management) capture the semantic containment of unstructured documents and their relationship with other corporate information and data, but structured vocabularies, such as domain taxonomies, can be tagged and traced throughout the semantic bulk dynamically contained within the semantic hyperspace. This yields alternative pattern segmentations that can serve as Domain-specific viewpoints for knowledge segmentation and analysis purposes.

ViewPoint profiling
By combining documents through their kSigs, we can generate Semantic ViewPoint profiles that can be used to view knowledge information from various perspectives through the semantic containment metaphor. We can further constrain semantics by applying structured vocabulary filters such as domain taxonomies. And we can leverage meaningful concept patterns discovered from these First Order Knowledge Operations as Second Order Knowledge Operators in order to assimilate higher-order knowledge object derivatives.

Semantic ViewPoints permit us to "mix and match" knowledge information from various perspectives so that we can facilitate deeper learning experiences from the information at hand. We can also uncover repeating patterns of knowledge usage with a relative confidence in the possible impact of their re-usage, as can be determined through cause-effect-impact semantic pattern analysis.

We can create "named" profiles, such as user interest and knowledge profiles. We can also assign role-based profiles and combine interest and knowledge profiles to highlight, track, and manage collaborative knowledge sharing profiles reflected within the concept pattern formations. Through these Second Generation Knowledge Management tools, we can derive the impact of learning across corporations and on targeted projects and use these effective patterns to build corporate knowledge acquisition and learning curriculums that are sensitive to what works and what doesn't, who the experts and mentors are, who needs to have knowledge, when, who are the more effective teams to work on business projects together, and much more.