Research on Semantic Analysis of Ocean Flow Field Based on Feature Similarity Collaborative Filtering

Abstract

Ding, L., 2020. Research on semantic analysis of ocean flow field based on feature similarity collaborative filtering. In: Yang, D.F. and Wang, H. (eds.), Recent Advances in Marine Geology and Environmental Oceanography. Journal of Coastal Research, Special Issue No. 108, pp. 53–57. Coconut Creek (Florida), ISSN 0749-0208.In the field of ocean space-time data modeling research, fields and features are usually used to describe and organize ocean current phenomena, which is continuous and dynamic. However, during the process, the semantic analysis and expression of ocean flow field phenomena often produce heterogeneous problems. Because the feature theory can construct and define the conceptual model framework of domain knowledge system, the semantic analysis of the ocean flow field using the feature theory can be regarded as one of the ways to achieve the semantic sharing of the ocean flow field. Moreover, based on the collection and analysis of existing knowledge and concepts in the field of marine science, a quadruple-based organization in the paper is proposed for ocean flow field features, in which by expanding the concept features, attribute features, and relationship features, a basic structure-based approach is formed. The overall characteristic structure of the ocean flow field comprises concept, attribute, and relationship structure. Additionally, collaborative filtering is performed on the similarity of the structural features in the ocean flow field, and a formal grammatical expression system conforming to the characteristics of continuous flow field is also made so that a normative framework system is provided for the ocean flow field knowledge organization. The OWL language is used, which allows for the conduction of the formal expression and description of geostrophic flow, which provides semantic support for the integration and management of spatiotemporal data in the ocean flow fields.