Abstract
The natural language expression “near” describes spatial proximity. However, the interpretation of this expression depends on the context. In this thesis, we investigate how a context-dependent model for “near” can be formulated. For doing so, we investigate the following questions: (i) what is the relevant contextual information for “near”? (ii) how does the identified information influence the interpretation of near? To answer these questions, the research conducted consists in identifying the relevant contextual information from the literature. Subsequently, different contextualized nearness models are formulated to evaluate the influence of the context on “near”. To train the contextualized nearness models, the necessary data is extracted from the geograph.co.uk corpus. The data is extracted using a probabilistic semantic geo-parser, which we built on the basis of the insights gained in this thesis.
Novel, Marc