期刊
DATA & KNOWLEDGE ENGINEERING
卷 141, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.datak.2022.102054
关键词
Graph-based model; Hierarchical representation; Knowledge extraction; Maritime mobility; Network analysis
This paper presents a hierarchical graph-based model for representing moving objects and trajectories, which is implemented and experimented with historical maritime data. Experimental analyses reveal knowledge patterns from the hierarchical graph database, and queries applied to an European maritime network derive mobility patterns and highlight network structures.
Hierarchical representations of transportation networks should provide a better understanding of mobility patterns and the underlying structures at various abstraction levels. This paper introduces a hierarchical graph-based model for representing moving objects and trajectories according to multiple spatial, temporal and semantic scales. This formal model is implemented in a graph database and experimented with historical maritime data. Several experimental analyses explore and extract knowledge patterns from the hierarchical graph database. A series of queries applied to an European maritime network derive mobility patterns and highlight network structures.
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