Additional clarification of the Genius Research idea.
Parts have been revised for simplicity and to try to express the big picture.
TERMS:
MASTER TABLE - Every artist, work, occurrence (Subject Of Analysis); "Semantic Containers" are manually (trained) sorted in a hierarchical fashion. Semantic containers overlap.
SUBJECT OF ANALYSIS - Every artist, work, occurrence
SEMANTIC CONTAINERS - Biography, Intention, Religion; semantic attributes related to the subject of analysis
PAGE ANNEX - Master Table corpus
PULL STRIP - When you gather "Semantic Container" elements from the master table for specification under a "Subject of Analysis" your "Pull Strip" alters the content of the "Master Table".
SEMANTIC STAFF - stamp/syllogism construction method; interacts with "Pulls Strips" to add data to "Semantic Containers".
How it Works?
Master Table info is posited through "Pull Strips", one of various "semantic staffs" interact with a "Pull Strip" to create information for the master table.
Chopping problem: Different "Semantic Staffs" will analyze different quantities of information. For example: "The quick brown dog jumped over the lazy red fox" could be analyzed word by word, or by noun/verb couplet, or by the whole sentence, or as a part of a whole idea, etc... This is "floating point analysis" and it's an important meme.
The information derived will be appropriated to the same "Semantic Container" but there will be somewhat problematical "Break-Down Ratio Clusters"; these are represented as overlap in the same semantic container due to the same "Subject of Analysis" being interpreted through multiple "Semantic Staffs" that deal with different quantities of information. Overlap will be marked as a "Cluster"; merging of "Cluster" information is important because the "Remainders" become important anomalies.
If Genius.com/theinternet has a cloud layer of data through it’s shadowpage extensions; this would be an “inverted version inside of Genius as opposed to outside” that would serve as a manipulable string of infinite relations that can be isolated and utilized to serve various “statistical ends” including creating an ever growing “plausibility machine” for any given statement about anything in relation to all the information in it’s “semantic Container String”.
This could turn it into a serious “world research platform” where discoveries are posited directly into our corpus; it will also add a 3rd dimension to the annotation process that allows us to explore controversy in depth, rather than just back and forth arguments.