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KMS, an abbreviation of Knowledge Management System, was a commercial second generation hypermedia system, originally created as a successor for the early hypermedia system ZOG. KMS was developed by Don McCracken and Rob Akscyn of Knowledge Systems, a 1981 spinoff from the Computer Science Department of Carnegie Mellon University.
The analysis highlights Art, Science and Products as prominent areas in the source structure around KMS (hypertext).
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See recurring relationship patterns around KMS (hypertext) before inspecting the individual extracted relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
kms frames frame programs system links users text one items hypermedia always another also functionality current annotation knowledge akscyn originally
TTTA extracted 7 structured relationships around KMS (hypertext). Examples in this analysis include presentations → instance of → KMS was intended to represent all forms of explicit 'knowledge artifacts' and documents → instance of → opting instead for larger aggregates. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| presentations | instance of | KMS was intended to represent all forms of explicit 'knowledge artifacts' | 0.80 | text |
| documents | instance of | KMS was intended to represent all forms of explicit 'knowledge artifacts' | 0.80 | text |
| databases | instance of | KMS was intended to represent all forms of explicit 'knowledge artifacts' | 0.80 | text |
| and software programs | instance of | KMS was intended to represent all forms of explicit 'knowledge artifacts' | 0.80 | text |
| as well as common forms of electronic communication | instance of | KMS was intended to represent all forms of explicit 'knowledge artifacts' | 0.80 | text |
| documents | instance of | opting instead for larger aggregates | 0.80 | text |
| programs to be structured as hierarchies | instance of | opting instead for larger aggregates | 0.80 | text |
The concept neighborhoods around KMS (hypertext) bring nearby vocabulary together. In this analysis, examples include System, Also and Annotation. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Bridges highlight paths between different parts of the KMS (hypertext) map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around KMS (hypertext) to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Art, Science & Products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — KMS (hypertext) · EN edition · Analysis: TopicsToTalkAbout