Spatial Reasoning for Determining the Domain of the Set of Tags that Represent Geographic Objects

Eduardo Loza-Pacheco*, Miguel Torres-Ruiz** y Giovanni Guzmán-Lugo***

Los autores trabajan en el Centro de Investigación en Computación del Instituto Politécnico Nacional, Av. Juan de Dios Bátiz, s/n, UPALM-Zacatenco, 07738, México D.F., México (email: *eduardo.loza@gmail.com, **mtorres@cic.ipn.mx, ***jguzmanl@cic.ipn.mx).

Manuscrito recibido el 9 de marzo de 2012. ]]> manuscrito aceptado el 7 de mayo de 2012.

Resumen

Actualmente, existe una gran cantidad de información geográfica, proveniente de diversas fuentes como imágenes de satélite, fotografías aéreas, mapas, bases de datos, entre otras. Estas fuentes proporcionan una descripción exhaustiva de los objetos geográficos. Sin embargo, la tarea de identificar el dominio geográfico al que pertenecen involucra un procesamiento semántico, el cual está basado en la conceptualización de un dominio, lo que permite interpretarlo de una manera similar a como los seres humanos reconocen a las entidades geográficas y evitar así la vaguedad. Este trabajo propone un método para realizar un proceso de razonamiento espacial cualitativo en representaciones geográficas. El método se basa en el conocimiento a priori del dominio, el cual se encuentra explícitamente formalizado a través de una ontología. El conocimiento descrito en la ontología se valora de acuerdo con un conjunto de etiquetas que pertenecen a algún tipo de dominio geográfico para realizar el análisis semántico correspondiente y mapear esas etiquetas con los conceptos definidos en la ontología. Como resultado, se obtiene un conjunto de dominios geográficos ordenados por su relevancia, para proporcionar un concepto general relacionado directamente con las etiquetas de entrada, simulando la forma en que cognitivamente percibimos algún dominio geográfico en el mundo real.

Palabras Clave: Inteligencia artificial y computacional, sistemas inteligentes, adquisición de conocimiento, representación de conocimiento.

Abstract

Nowadays, there is much geospatial information from different sources such as satellite images, aerial photographs, maps, databases, and so on. It provides a comprehensive description of geographic objects. However, the task to identify the geographic domain to which it belongs is not simple, because this task involves semantic processing based on a conceptualization of a domain. It allows us to understand information in a way similar to how humans recognize the geographic entities and avoid vagueness. We propose a method for qualitative spatial reasoning in geospatial representations.

The method is based on a priori knowledge, which is explicitly formalized through an ontology. The knowledge described in the ontology is assessed according to a set of tags that belong to any geographical domain for semantic analysis, to map those tags to concepts defined in the ontology. As a result, a set of geographic domains in order of relevance is obtained, for providing a general concept directly related to the input tags, simulating the way in which humans cognitively perceive a geographic domain in the real world.

Key words: Computational and Artificial Intelligence, Intelligent Systems, Knowledge Acquisition, Knowledge Representation.

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AGRADECIMIENTOS

Este trabajo ha sido auspiciado y apoyado por el Instituto Politécnico Nacional (IPN), el Consejo Nacional de Ciencia y Tecnología (CONACYT) y la Secretaría de Investigación y Posgrado del IPN, a través de los proyectos: 20113712, 20113757, 20120563 y 20120482.

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