Frederick S Reed

US Patent:

6389406, May 14, 2002

Filed:

Dec 22, 1999

Appl. No.:

09/469833

Inventors:

Frederick W. Reed - Honey Brook PA
Duane J. McCrory - Malvern PA
John C. Waller - Plainfield CT
Charles Austin Parker - Exton PA
Eugene David Pendergraft - late of Jasper AZ

Assignee:

Unisys Corporation - Blue Bell PA
Autognomics Corporation - Norwich CT

International Classification:

G06F 1700

US Classification:

706 46, 706 45

Abstract:

A semiotic decision making system operates to respond, for example, to natural language queries. The system operates independent of the type of symbolic elements in which queries are cast. A training corpus of information in the form of sequential sets of a selected type of element is input to the system and processed by a semiotic processing module to create a knowledge database based upon the lineal relationship of elements within the training corpus. The knowledge database is then used to make decisions relating to queries input in the same type of elements. Accordingly, inputting a French training corpus results in a knowledge base useful in answering French questions. Multiple semiotic processing modules may be used to enhance performance.

US Patent:

6505184, Jan 7, 2003

Filed:

Jul 30, 1999

Appl. No.:

09/364191

Inventors:

Frederick W. Reed - Honey Brook PA
Charles Austin Parker - Exton PA

Assignee:

Unisys Corporation - Blue Bell PA
Autognomics Corporation - Norwich CT

International Classification:

G06F 1518

US Classification:

706 47, 706 45, 706 46

Abstract:

A sensor module is for use in a semiotic processing system. The sensing module receives data in a pre-specified format. It identifies sequential elemental symbols in the received data. First order sets of identified sequential element symbols are defined such that no first order set has more than a maximum number of sequential elemental symbols. Second order sets of sequential first order sets are defined such that no second order set has more than a maximum number N of sequential first order sets.

US Patent:

62758179, Aug 14, 2001

Filed:

Dec 22, 1999

Appl. No.:

9/469836

Inventors:

Frederick W. Reed - Honey Brook PA
Duane J. McCrory - Malvern PA
John C. Waller - Plainfield CT
Charles Austin Parker - Exton PA
Eugene David Pendergraft - late of Jasper AZ

Assignee:

Unisys Corporation - Blue Bell PA
Autognomics Corporation - Buffalo NY

International Classification:

G06F 1518

US Classification:

706 45

Abstract:

A decision making system uses semiotic processing modules to transform a training corpus of information, in the form of sequential sets of symbols, into a knowledge database. The knowledge database is thereafter used to make decisions relating to queries input in the same type of training corpus symbols. In the knowledge base, the system stores data representations of analyses of subsets of the training corpus sets of sequential elements. The knowledge base data representations comprise predicates and elemental and non-elemental acts. An inductive processor recursively processes the training corpus sets by evaluating the relationship and frequency of occurrence of individual elements and sets of elements in the training corpus. After processing of the training corpus is completed, the resultant knowledge base is used to evaluate queries in a performance mode of operation.

US Patent:

62789872, Aug 21, 2001

Filed:

Jul 30, 1999

Appl. No.:

9/364192

Inventors:

Frederick W. Reed - Honey Brook PA
Duane J. McCrory - Malvern PA
Charles Austin Parker - Exton PA
Jane Campbell Mazzagatti - Blue Bell PA
John C Waller - Plainfield CT
Dana M. Zabilansky - Lyme CT

Assignee:

Unisys Corporation - Blue Bell PA
Autognomics Corporation - Norwich CT

International Classification:

G06F 1700

US Classification:

706 45

Abstract:

A semiotic decision making system processes a training corpus of information in the form of sequential sets of elements to create a database which is thereafter used to make decisions relating to queries input in the same type of elements. Sets of sequential elements of a training corpus are received. Ordered pairs of sequential elements and ordered pairs are identified. The ordered pairs include element/element, pair/element, element/pair and pair/pair ordered pairs, in a recursive semiotic process based on the statistical occurrence of element sequences in the training corpus sets whereby each ordered pair represents an n sequential element subset of a training corpus set defined by a set of nested ordered pairs. Constituent sets of ordered pairs and elements are identified for the training corpus sets. Each constituent set for a given training corpus set of n sequential elements has 2n-1 members including representations of each sequential element of the training corpus set and a set of nested subsets of ordered pairs where each sequential training corpus set element is included in one of said ordered pairs.