Unpublished paper – written 12/1/98)
The Autonomous Organization
of Data through Semiotic Methods
(Draft: 12/1/98)
Paul S. Prueitt
Abstract
Semiotically grounded
information technologies can be built with a model that has (1) metadata, (2)
mechanisms for computational reasoning, and (3) a formal theory about human
interpretation of information in context. Our theory of interpretation
is informed by historical developments from experimental neuropsychology and
from Russian applied semiotics. Computational reasoning is supported by
the data structures of Quasi Axiomatic Theory (QAT), related computational
voting procedures and adaptive technologies. The metadata in information
is developed through situational based Structural Activity Relationship (SAR)
analysis on the class of types developed from decomposition of examples into
substructural classes of causes. This model produces the means for real time
situational analysis about open complex systems and their control.
Full Paper
1.1:
Implications to Information Retrieval
1.2:
QAT and computational argumentation
1.3:
Applied semiotics and neuropsychology
1.4:
Outline of unfinished work
1.5:
Knowledge Management
1.6:
Ecological perception and thermodynamics
Section 2: The nature of
rules
2.1:
The use of adaptive technologies in the market place
2.2:
Block diagram for situational analysis
2.3:
The five interpretations
2.4:
Notes on iconic representation
Section 3: The Voting
Procedure
3.1:
The use of Mill’s logic
3.2:
Data structure for recording the votes
3.3:
A second data structure to record weighted votes
3.4:
Data structure to record the results
Section 4: Assembly, disassembly and structure
activity relationship analysis
Section 4: Assembly,
disassembly and structure activity relationship analysis
4.1:
Memory and learning
4.2:
Knowledge
4.3:
Pospelov’s notation
4.4:
Steady states and the first order cybernetic system
4.5:
The Russian Design for Applied Semiotic System.
References (not complete)