Authors:
Christos T. Rodosthenous
and
Loizos Michael
Affiliation:
Open University of Cyprus, Cyprus
Keyword(s):
Information Retrieval, Geographic Focus Identification, Knowledge Bases, Natural Language Processing, Geographic Information Systems.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Hybrid Intelligent Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Pattern Recognition
;
Soft Computing
;
Symbolic Systems
Abstract:
We consider the problem of identifying the geographic focus of a document. Unlike some previous work on
this problem, we do not expect the document to explicitly mention the target region, making our problem one
of inference or prediction, rather than one of identification. Further, we seek to tackle the problem without appealing
to specialized geographic information resources like gazetteers or atlases, but employ general-purpose
knowledge bases and ontologies like ConceptNet and YAGO. We propose certain natural strategies towards
addressing the problem, and show that the GeoMantis system that implements these strategies outperforms an
existing state-of-the-art system, when compared on documents whose target region (country, in particular) is
not explicitly mentioned or is obscured. Our results give evidence that using general-purpose knowledge bases
and ontologies can, in certain cases, outperform even specialized tools.