A Semantic Enhanced Model for effective Spatial Information Retrieval
This addresses challenges in retrieving geographic information from web and Spatial Data Infrastructures for users, but it appears incremental as it builds on existing ontology and semantic methods.
The paper tackles the problem of semantic heterogeneity in geographic information retrieval by proposing an ontology-based semantic enhanced model that explicitly represents metadata and provides linked RDF instances, resulting in improved searching and retrieval of ranked spatial search results.
A lot of information on the web is geographically referenced. Discovering and retrieving this geographic information to satisfy various users needs across both open and distributed Spatial Data Infrastructures (SDI) poses eminent research challenges. However, this is mostly caused by semantic heterogeneity in users query and lack of semantic referencing of the Geographic Information (GI) metadata. To addressing these challenges, this paper discusses ontology based semantic enhanced model, which explicitly represents GI metadata, and provides linked RDF instances of each entity. The system focuses on semantic search, ontology, and efficient spatial information retrieval. In particular, an integrated model that uses specific domain information extraction to improve the searching and retrieval of ranked spatial search results.