A differential notion of place for local search

ABSTRACT

For extracting the characteristics a specific geographic entity, and notably a place, we propose to use dynamic Extreme Tagging Systems in combination with the classic approach of static KR models like ontologies, thesauri and gazetteers. Indeed, we argue that in local search, the what that is queried is implicitly about places. However existing knowledge representation (KR) models, such as ontologies based on logical theories, conceptual spaces, affordance or other, cannot capture in isolation all aspects of the meaning of a place. Therefore we propose to use a combination of them based on the underlying notion of differences, linked elements of meaning without commitment to any KR model. Mapping to elements of different KR models can be made later to follow the requirements of a given task, supported by a KR representation of the elements that support this task. We show the usefulness of the approach for local search by applying it to the notion of place defined as a location that supports a homogeneous affordance field, i.e. the spatial area which allows me the do a particular thing, while allowing the homogeneity of movement, meaning that the previous field is not interrupted by any boundaries.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods

General Terms:
Algorithms, Experimentation, Human Factors, Reliability, Theory

Keywords:
AI, Wordnet, affordances, conceptual spaces, differences, extreme tagging, image schemata, knowledge representation, local search, multi-representation, similarity