Fuzzontology: Resolving Information Mining Ambiguity in Economic Intelligent Process

Human beings are seen as a problem solver, and the process follows the simple input-process-output. Thus having identified a decisional problem (input), will apply some rules of inference and problem solving techniques based on experience and cognitive abilities (processing) to deduce or arrive at some conclusion (output). Information is frequently defined as interpreted data. Juxtaposing with infological equation by Langefors, the importance of the interpreter becomes vivid in the process. Earlier on, we proposed an ontological framework for knowledge reconciliation in economic intelligence process. However, we noticed with deep concern that the various mental process shaping and constructing certain knowledge are difficult to comprehend and placed tangibly making it Fuzzy. This research work is based on the horrendous nature of the bi-valued logic (yes/no, true/false) inherently present in human attempt to inform. We therefore propose a new concept tagged Fuzzontology to assist in enhancing the interpretation of ambiguous meaning.

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