Using an Ontology-based Approach for Geospatial Clustering Analysis
نویسنده
چکیده
Geospatial clustering is an important method for geospatial information analysis. However, most clustering methods do not consider semantic information during the clustering process. In this paper, we present a formal geospatial clustering ontology framework, which can provide the background for geospatial clustering. Using the ontology, geospatial clustering can become a knowledge-driven process.
منابع مشابه
Density-Based Clustering with Geographical Background Constraints Using a Semantic Expression Model
A semantics-based method for density-based clustering with constraints imposed by geographical background knowledge is proposed. In this paper, we apply an ontological approach to the DBSCAN (Density-Based Geospatial Clustering of Applications with Noise) algorithm in the form of knowledge representation for constraint clustering. When used in the process of clustering geographic information, s...
متن کاملAn Executive Approach Based On the Production of Fuzzy Ontology Using the Semantic Web Rule Language Method (SWRL)
Today, the need to deal with ambiguous information in semantic web languages is increasing. Ontology is an important part of the W3C standards for the semantic web, used to define a conceptual standard vocabulary for the exchange of data between systems, the provision of reusable databases, and the facilitation of collaboration across multiple systems. However, classical ontology is not enough ...
متن کاملA Clustering Based Location-allocation Problem Considering Transportation Costs and Statistical Properties (RESEARCH NOTE)
Cluster analysis is a useful technique in multivariate statistical analysis. Different types of hierarchical cluster analysis and K-means have been used for data analysis in previous studies. However, the K-means algorithm can be improved using some metaheuristics algorithms. In this study, we propose simulated annealing based algorithm for K-means in the clustering analysis which we refer it a...
متن کاملA clustering approach for mineral potential mapping: A deposit-scale porphyry copper exploration targeting
This work describes a knowledge-guided clustering approach for mineral potential mapping (MPM), by which the optimum number of clusters is derived form a knowledge-driven methodology through a concentration-area (C-A) multifractal analysis. To implement the proposed approach, a case study at the North Narbaghi region in the Saveh, Markazi province of Iran, was investigated to discover porphyry ...
متن کاملIntegrating distributed data grid, ontology and Web-based workflow technologies into geospatial cyberinfrastructure: system design and case study
Geospatial research increasingly relies on shared geospatial data, interconnected models and successively refined analysis which requires not only more powerful but also more accessible cyberinfrastructure systems for support. In this study, we propose to integrate data grid, ontology and Web-based workflow technologies to build more accessible cyberinfrastructure systems for geospatial computi...
متن کامل