A common sense geographic knowledge base for GIR

As background knowledge of geographic information retrieval (GIR), the gazetteers have their limitations. In this paper we propose to develop and implement a common sense geographic knowledge base (CSGKB) instead of the gazetteers. We define that CSGKB is concerned with the representation of geographic knowledge in human brain and the simulation of geographic reasoning in daily life. Traditional geographic information system (GIS) is based on the model of map with its data based on geographic coordinates and its computation based on geometry. However, CSGKB, which is made up of geographic features and relationships and is based on qualitative spatio-temporal reasoning, can be viewed as the direct model of geographic world. This paper also discusses the characters of CSGKB and presents its structure which is composed of knowledge base, inference engine, geographic ontology and learner. The applications using CSGKB include geographic information retrieval (GIR), natural language processing (NLP), named entity recognition (NER), Semantic Web, etc. At present, our work focuses on the design of geographic ontology and the implementation of the CSGK13 knowledge base. In this paper we describe the CSGKB ontology structure, top ontology, geographic location ontology, spatial relationship ontology, and domain ontologies. Finally, we introduce the current state of implementation of CSGK13 and give an outlook on our future researches.