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OSI KOS System description

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  • Paul Prueitt
    System description The OSI Knowledge Operating System (KOS) develops capabilities for tracking global trends and anticipating events. The system brings
    Message 1 of 2 , Aug 1, 2002
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      System description

      The OSI Knowledge Operating System (KOS) develops capabilities for tracking
      global trends and anticipating events. The system brings together a variety
      of innovative components to provide an "intelligence-vetting engine" that
      globally tracks emerging ideas around any selected topic and around specific
      event types. The OSI KOS is used in patent trending to provide an economic
      engine for a community of knowledge scientists operating under the
      principles laid on in the Behavioral Computational Neuroscience Group
      (BCNGroup) (1997) Chapter.

      Collection – OSI KOS systems will automatically monitor information flow in
      the Internet on a 24/7 basis, looking for new items that are related to the
      subject and event areas that we track. Smart mobile programs look for new
      and novel relationships not previously anticipated and send data structures
      into centralized information vetting systems, staffed by humans. For
      example, all Internet published scientific conferences in a specific area of
      interest might be mined for trending analysis of intellectual property
      trends. Conceptual mining is language independent. Thus human annotation of
      emerging concept trends can be done in one’s native language and the
      annotation incorporated into a single generalized cA/eC index (knowledge
      base). Language independent topic maps are constructed using the OASIS
      standard for topic maps. KOS systems can also be pointed at scientific data
      sources or repository of text such as patent repositories or e-forum text.

      Storage - Our collected information is stored in categorical abstraction and
      event chemistry formats that allow the content of records (a source of data)
      to be directly related to any (and all) other records (data sources). The
      devices map the structural coupling of the collected information. They
      serve as indices and generalized indices. The maps are cA/eC data
      structures that are independent second order control mechanisms used in
      information query and routing using cA and anticipatory responses. A
      tri-level architecture is used that separates categorical abstraction (cA)
      from an event knowledge base. Event Chemistry (eC) then results from the
      aggregation of cA under the constraints of the existing event knowledge
      base.

      Extraction - A number of mature technologies extract information from data
      sources. This information is diffused into a substructure layer (cA) of
      information that serves the agile reconstruction of information in context
      (eC). The agile technology allows us to look at an object of investigation
      from many different perspectives. The extraction process is represented as
      categorical invariance in the patterns of word expressions and processed
      into a central (small) knowledge base. The size of the knowledge base is
      due to our use of categorical abstraction methodology. Information
      compression, routing and extension (inference) processes are achieved using
      an In-Memory Referential Information Base system (I-RIB) that denotes a
      graph structure containing the structural relationship that have been found
      to exist in the data.

      Analysis - A number of analytical tools automatically develops ontologies
      and taxonomies. But in cA/eC systems, logical and structural relationships
      are rendered visually and with auditory sounds. The operating structure of
      a given area of knowledge - such as "national security" is visually
      rendered. Various scenarios are generated based upon the intrinsic
      functions of components of the system. Humans are assisted in exploring
      variations in strategies and in storing work product related to these
      investigations. Knowledge management specialists can study Human
      Information Interactions (HII) with the system’s second order control
      system.

      Simulation and senseMaking – The display of cA/eC pushes the cognitive load
      away from the AI computer programs and onto the capable hands of humans.
      The notion of formal deduction is replaced with an extension of
      quasi-axiomatic theory (to replace the expert system technologies) and human
      visual and auditory experience of cA/eC. What if scenarios and conjectures
      about causes take a new form where humans in small communities develop human
      language meaning based on the discussions about the various cA/eC defined
      event structures.

      Display – The KOS provides breakthrough capabilities for identifying and
      monitoring early indicators of significant change. Visualization of the
      categories of data and relationship between this data enhances the ability
      of analysts to develop anticipation of emerging events.


      ***

      Please send comments to

      http://groups.yahoo.com/group/categoricalAbstraction
    • Mark
      Attention All Members of Nantech and Categorical Abstraction Online Message Board Community, In regard to the message pertaining to Categorical Abstraction,
      Message 2 of 2 , Aug 2, 2002
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