Artificial Intelligence - Special issue: Fuzzy set and possibility theory-based methods in artificial intelligence
A computational view of the cognitive semantics of spatial prepositions
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Reconstructing spatial image from natural language texts
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 4
ANTLIMA: a listener model with mental images
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Ontological diversity: the case from space
Proceedings of the 2010 conference on Formal Ontology in Information Systems: Proceedings of the Sixth International Conference (FOIS 2010)
A linguistic ontology of space for natural language processing
Artificial Intelligence
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The problem we want to handle in this paper is vagueness. A notion of space, which we basically have, plays an important part in the faculty of thinking and speech. In this paper, we concentrate on a particular class of spatial descriptions, namely descriptions about positional relations on a two-dimensional space. A theoretical device we present in this paper is called the potential model. The potential model provides a means for accumulating from fragmentary information. It is possible to derive maximally plausible interpretation from a chunk of information accumulated in the model. When new information is given, the potential model is modefied so that that new information is taken into account. As a result, the interpretations with maximal plausibility may change. A program called SPRINT(SPatial Relation IN-Terpreter) reflecting our theory is in the way of construction.