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KNOWLEDGE MANAGEMENT
Increase your productivity by controlling context
By Bain McKay
With the competitive terrain of today's knowledge-based economy changing at a faster pace than ever before, it's essential that corporations track meaningful changes early in their development to gain and sustain competitive advantage. Core competency management is an active measure of a corporation's ability to productively distribute its knowledge to projects and employees in need, ensuring that the right knowledge on key projects is available to the right staff, in a timely manner. Core competency management facilitates the delivery of a quality product. As a result, knowledge management is really about core competency management.
The color of knowledge In past articles I wrote about document knowledge signatures as context trees that can be automatically generated from the content of the document. I discussed how you can automatically highlight key phrases in and across documents using XML (eXtensible Markup Language) with XSL (eXtensible Style Language) style sheets, and how we can assign color codes to types or classes of knowledge to quickly lift the representation of knowledge classes as colored bands. And we discussed how such methods could facilitate speed-reading results for those who aren't trained in such highly productive knowledge assimilation skills.
This ability to generate a knowledge tree as a descriptive signature of the knowledge within a document is fundamental to uncovering and leveraging the power of knowledge in text. Since all knowledge trees eventually end up being interconnected by their similarities through intermediary knowledge trees, you end up with an organic latticework that facilitates continuous exploration and learning, similar to how the brain works.
Three knowledge classes There are three classes of knowledge: tacit, explicit, and declarative:
- Tacit knowledge is reflected by expressing usage pattern convergences across document collections in tree-like rule forms;
- Explicit knowledge in structured documents is expressed by simple subject-predicate tagging rules (e.g., IF <A> THEN <B>);
- Declarative knowledge is much more comprehensive, expressing semantic constraints as a hierarchically linked set of tagging rules chained together in a tree-like fashion, much like a management decision tree (also known as a Baysean Statistics Tree).
These knowledge classes support each other. Where a document is structured through XML Zoned Tagging and Explicit or Declarative Expert Rules, Tacit Knowledge Rule reflection can be used to further detail context through additional automatic XML tagging of unstructured DOM (Document Object Model) context components. As a result of this symbiotic relationship between Tacit, Explicit, and Declarative Knowledge Classes, the knowledge able to be harnessed in document collections can be significantly enhanced.
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