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George Bradford

Semantic Networks - 0 views

    • George Bradford
       
      The reductionist approach: applied in this way it's to facilitate "findability" where otherwise information discovery and retrieval might be 'too' long. The dilemma is that once the machine finds potential useful material, we are left to decide on its pertinence or relevance.
  • The goal of the system is to make all marketing information and insights generated by the man/machine interaction available to the user, so that there is a convergence towards a "conservation of information".
    • George Bradford
       
      The reductionist approach: applied in this way it's to facilitate "findability" where otherwise information discovery and retrieval might be 'too' long. The dilemma is that once the machine finds potential useful material, we are left to decide on its pertinence or relevance.
  • The network in Figure 7 becomes very complex with a 100-fold increase in the amount of information.
    • George Bradford
       
      It's easy to extrapolate how 'real' materials will carry such levels of complexity that the semantic processing of it will quickly become impossible: the embedded structure is too great for current processing strategies, so work arounds are what everyone is doing. But we need now strategies and tools that improve upon the Google search model: we don't have the time to properly mine the material to ensure the quality of our work. We don't have the time to wait until computer technologies are 100's of times more powerful than at present.
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    This document concerns the management of the output of insight generators, the software agents utilized in the insight generation systems. The solution to managing these reports involves the automatic creation of a repository for all materials generated by various insight generators; this repository allows the user to navigate through this continually growing space of marketing reports, gaining new insights about the relationships between items of interest and adding new insights in the process. The goal of the system is to make all marketing information and insights generated by the man/machine interaction available to the user, so that there is a convergence towards a "conservation of information". To use a geometric metaphor, the goal is to make the user equidistant from all information at all times, as illustrated below.
George Bradford

Semantic Networks - 0 views

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    John F. Sowa - This is a revised and extended version of an article that was originally written for the Encyclopedia of Artificial Intelligence, edited by Stuart C. Shapiro, Wiley, 1987, second edition, 1992. A semantic network or net is a graphic notation for representing knowledge in patterns of interconnected nodes and arcs. Computer implementations of semantic networks were first developed for artificial intelligence and machine translation, but earlier versions have long been used in philosophy, psychology, and linguistics. What is common to all semantic networks is a declarative graphic representation that can be used either to represent knowledge or to support automated systems for reasoning about knowledge. Some versions are highly informal, but other versions are formally defined systems of logic. Following are six of the most common kinds of semantic networks, each of which is discussed in detail in one section of this article.
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