Topical and Spatio-Temporal Search over Distributed Online Databases

In this chapter, the authors propose a novel framework for the support of multi-faceted searches over distributed Web-accessible databases. Towards this goal, the authors introduce a method for analyzing and processing a sample of the database contents in order to deduce the topical, the geographic, and the temporal orientation of the entire database contents. To extract the database topics, the authors apply techniques leveraged from the NLP community. To identify the database geographic footprints, the authors first rely on geographic ontologies in order to extract toponyms from the database content samples and then employ geo-spatial similarity metrics to estimate the geographic coverage of the identified toponyms. Finally, to determine the time aspects associated with the database entities, the authors extract temporal expressions from the entities’ contextual elements and utilize a time ontology against which the temporal similarity between the identified entities is estimated. DOI: 10.4018/978-1-61692-868-1.ch013