Qualitative spatial reasoning on topological relations by combining the semantic web and constraint satisfaction

Abstract

Qualitative spatial reasoning on topological relations can extract hidden spatial knowledge from qualitatively described topological information, which is of significant importance for decision-making and query optimization in spatial analysis. Qualitative reasoning on spatial topological information based on semantic knowledge and reasoning rules is an efficient means of reducing both the known relations and the corresponding rules, which can result in enhanced reasoning performance. This paper proposes a qualitative reasoning method for spatial topological relations based on the semantic description of reasoning rules and constraint set. Combined with knowledge from the Semantic Web, the proposed method can easily extract potential spatial results consistent with both unique and non-unique rules. The Constraint-Satisfaction-based approach, describing constraint set with semantic expressions, is then used together with an improved path consistency algorithm to verify the consistency of the unique-rules-based and non-unique-rules-based reasoning results. The verification can eliminate certain reasoning results to ensure the reliability of the final results. Thus, the task of qualitative spatial reasoning on topological relations is completed.