THINK: "Knowledge Mining", outside the box.
- Nicholas Zendelbach
International Cognitive Computing
1000 Rainbow View Drive (PO Box 602)
Lakeside, Arizona 85929
Web site: www.cambo1.com
Abstract of the Disclosure.
The invention's name is CAMBO an acronym for Computer Aided Management By Objective. The title is a "multi-EXPERT System Generator", and the vision an "artificial intelligent bridge" between technology and the ability to automate the instruments of the MBO methodology, namely: Charters, Organization Charts, Operational Plans, Project Management, Performance Planning and others all containing the knowledge, expressed in 'English Grammatical Sentences', upon which an enterprise conducts business. It would require the design of a unique combination of advanced methodology and technology capabilities built upon and work in concert with current state of the art, 'Data Normalized', Relational Data Base structure. The "AI Bridge" would include an advanced methodology for Normalizing Knowledge, a unique definition for a unit or element of knowledge, an advanced structure for a Spatial Relational Knowledge Base and a 5th generation programming language to support a Natural Language Processing interface. A successful CAMBO installation video is available.
Patent pending application renewed September 2009 for 2010. Documents attached refer to original 2008 patent pending application.
Non-Provisional (Utility) Patent.
Specification. See CAMBO, customer video presentation of an installed and operating multi-EXPERT system and Natural Language Processing interface.
Title of the Invention.
Applicant: Nicholas Joseph Zendelbach, US Citizen, Lakeside, Arizona, 85929. Invention: A Computer, multi-EXPERT System Generator, to include:
· Knowledge Engineering Storyboard Methodology.
· New paradigm: Knowledge Normalization for Spatial Relational Knowledge Base.
· 5th Generation Programming Language LIPS1 (Language Instruction Per Sentence).
· Natural Language Processing, methodology.
Background of the Invention. See: Introduction Section and CAMBO History Video, narrated by Nicholas Zendelbach.
Brief Summary of the Invention. See: Section ONE, Methodology.
Detailed Description of the Invention.
o Section TWO, Knowledge Engineering, TQM2 and BCL.
o Section THREE, Rule Writing.
o Section FOUR, Business Applications.
o Examples: Knowledge Engineering Storyboard, Military Application (NEMISYS), Artificial Intelligent (AI) Human GENE Research, Brain Mapping,72 billion dollar, Silicon Valley, County Assessor.
Thank you for reviewing my design work titled, CAMBO an acronym for Computer Aided Management By Objective. The name was chosen because I envisioned an artificial intelligent bridge between technology and the ability to automate the instruments of the MBO methodology, namely: Charters, Organization Charts, Operational Plans, Project Management, Performance Planning and others all containing the knowledge, expressed in 'English Grammatical Sentences', upon which an enterprise conducts business. It would require the design of a unique combination of advanced methodology and technology capabilities built upon and work in concert with current state of the art, 'Data Normalized', Relational Data Base structure.
The AI Bridge would require four sections;
1. A new methodology for normalizing knowledge elements.
CAMBO: new paradigm for 'Knowledge Normalization'. Knowledge Engineering Storyboard and P3 models=4 Prime Domains of Knowledge.
2. A new definition for a knowledge element.
CAMBO: a single knowledge element is a single 'English Grammatical Sentence', expressed as a single rule, that when composed with other 'English Grammatical Sentences' combine to form a 'Rule Set'.
3. A new design for a knowledge relational base.
CAMBO: Spatial Knowledge Relational Base structure, dimensional P3 models processing relational Rule Sets.
4. A new knowledge access method.
CAMBO: Natural Language Processing, 5th Generation programming language: LIPS1 (Language Instructions Per Sentence), LIPS2 (Logical Inference Per Sentence) and MECA (Multi Expert Consanguine Analyzer).
From: PROTOTYPE MODELS TO OPERATIONAL SYSTEM.
See CAMBO, customer video presentation of an installed and operating multi-EXPERT system and Natural Language Processing interface.
Having demonstrated the operability of the CAMBO design for a multi-EXPERT system with a Natural Language Processing interface, the foundation has been laid to juxtapose the watershed created by the development of a Data Normalization methodology (Entity Relationship, Canonical Synthesis) for designing a Relational Data Base structure, with the CAMBO watershed, Knowledge Normalization for designing a Relational (Spatial) Knowledge Base structure.
The value in this invention is four fold.
· First, the ability to: Identify, Capture, Codify and Relate 'knowledge', in a Natural Language opens the door for one person to access the combined talents, skills and experiential knowledge of many human experts.
· Second, planning: project management, scheduling resources, organizing resources and directing resources will be predicated upon knowledge relationships in concert with data relationships. The kernel logic here is simply that when a computer executes knowledge, in the form of rule sets, the results are presented as data, which in turn gives direction to those rule sets requiring change.
· Third, the development of systems based upon the new foundation of 'Relational Knowledge' in a Natural Language interface will reach beyond the business enterprise arena to all forms of human endeavor. An example is medical research, for which growth and direction is guided by the results produced from experiments. The ability to: Identify, Capture, Codify and relate these results will exponentially increase the ability to discover, translate and apply treatment modalities. (see section titled 'AI Gene Research')
In the field of engineering (see client demonstration video), the knowledge of senior engineers can be passed onto junior engineers, as it would apply with all fields of human endeavor, knowledge need not be forgotten or lost. A computer Spatial Relational Knowledge Base is the foundation upon which new knowledge is constantly updated becoming the 'shoulders upon which we can stand and see farther'.
· Fourth, the installation of knowledge based systems in differing human endeavors will have the effect of unifying human experiential knowledge and providing the ability to cross reference a more cognitive and meaningful view of the subject matter.
In 2001 Industrial Design Corporation, Tempe, AZ, asked International Cognitive Computing to design an ERP system that would capture the rules by which their engineers conducted business? The ERP initiative for this project is 3 fold.
First, that due to the cyclical nature of the semiconductor industry, IDC has been required to hire and layoff engineers, placing them in an almost constant state of talent searching (a bottleneck for developing an ERP application).
Second, the uniqueness of the skills required is compounded by the varying engineering and scientific disciplines involved in a single customer order (another bottleneck for developing an ERP application).
Third, IDC management has a strong ERP strategic direction that includes the automation and retrieval of the rules by which their senior engineers (in all disciplines and sciences) makes decisions about elements of a customer requirement.
The IDC Story: The First Successful AI Based Multi-Expert System in Arizona.
Examine a multi-expert system generator, Rose Navigator, and an Enterprise Resource Plan to help manage the need for human engineers against the dynamics of customer expectations and orders.
Pages: 39 through 45, also pages 1 and 5.
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This next PCAI magazine article is a behind the scenes look at the technology utilized in the Tempe project.
Natural Language Processing begins with knowledge normalization.
JUNE 2004 Publication: PCAI Magazine.
The Heuristic Life Cycle of a multi-Expert system.
Introduction, the purpose of this article is to introduce a new paradigm in the discipline of engineering human knowledge.
This article introduces a new paradigm to the discipline of engineering human knowledge, one that we divide into four tenets of knowledge representation:
1. The four prime domains of knowledge.
2. All human knowledge has, at its root, a language to communicate the knowledge.
3. A single language sentence contains the smallest unit of knowledge, and it is possible to normalize and codify this unit of knowledge into a multi-expert computer system (Language representation).
4. A knowledge based computer system can learn as well as teach.
This paradigm, as illustrated in this article, is the result of research and development and the resulting creation of a multi expert system generator. The methodology of the multi-expert system generator is a self-designing system it constructs and designs attributes that are an integral part of the methodology, process and architecture used to generate the multi-expert system.
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