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Near & Far

Near & Far. Stefan Hahmann Alexander Padberg Christian Mayer Aneta Florczyk Ontology and Vagueness Tutor: Brandon Bennet IFGI Spring School, 21-31 March 2010, Muenster, Germany. NEAR “not far distant in time or space or degree or circumstances” Simple Ambiguity Almost

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Near & Far

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  1. Near & Far Stefan Hahmann Alexander Padberg Christian Mayer Aneta Florczyk Ontology and Vagueness Tutor: Brandon Bennet IFGI Spring School, 21-31 March 2010, Muenster, Germany

  2. NEAR • “not far distant in time or space or degree or circumstances” • Simple Ambiguity • Almost • Examples of ambiguity • "near neighbors" • "a near hit by the bomb" • "in the near future" • "they are near equals" • "a very near thing" • "she was near tears" • "his nearest approach to success“ Natural Language Definition “Near”

  3. FAR • “located at a great distance in time or space or degree” • Examples of ambiguity • "we come from a far country" • "far corners of the earth" • "the far future" • "a far journey" • "the far side of the road" • "far from the truth" • "far in the future“ Natural Language Definition “Far”

  4. Physical • Geometric Distance - relative (context) and subjective interpretation • Historical • Changed due to the changes of the way of traveling • Functional • Common way of describing distances • Legal/Conventional • Restriction (law or regulation) • E.g. German case: reimbursement for commuters (if distance to work is more than 20 km) Modes of Classification

  5. Nearness • Farness • Nearness and Farness are interpretations of distance Goal

  6. Light green: area reachable by car in five minutes

  7. Parameters of Variability Effort Spatial gap Time Financial cost Context Scale Size Significance

  8. Effort Spatial gap

  9. Context Scale

  10. Context Size

  11. Predication criteria Individuation take all possible objects and arrange them in pairs of two Demarcation whether a pair of objects is considered far apart or near to each other is determined via a threshold Identity whether a distance is conceived as far or near might change if context or effort change over time

  12. Human farness = f(context, effort) nearness = f(context, effort) Geometric farness = f(context) nearness = f(context) Temporal farness = f(context) nearness = f(context) Approach

  13. farness ~ [f(effort) * scale] / [size * significance] nearness ~ 1 / farness Definitions

  14. Axioms Precondition: context = CONSTANT Axiom1: all x1 all y1 all x2 all y2 ( effort( near(x1,y1) ) < effort( far(x2,y2) ) ) Axiom2: all x all y all z ( near(x,y) & near(y,z) -> ¬far(x,z) )

  15. VAGUE!!! Conclusion

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