Structural modeling of spatial information in texts and semantic localization

doi:10.11947/j.AGCS.2023.20220066

Abstract

Abstract: A large number text including spatial information exist widely on the Internet. In order to solve the problems of inconsistent spatial semantic modeling methods and inappropriate fuzzy processing methods for describing the location of events in those text, this paper uses the square discrete grid to establish a structured semantic expression model, and uses a unified form to express three basic semantics (direction, distance and topology). The convolution method is used to quantify the fuzzy concepts in the spatial semantics, and the uncertain semantic description is projected to the geographical space, and finally the geographical location of the event is determined through the multi-sentence spatial semantics. Experiments show that: ① The structured semantic representation model can be applied to semantics with various types of spatial information, and can determine the geographic range of unknown events when multi-semantic joint modeling and merging; ② The credibility of semantic location is related to the semantic type, the type of reference entity, the number of reference entities, the proportion of correct semantics and other factors. When the number of reference entities is large, the geographical location range of events can be determined under the condition that the number of correct semantics is less than that of wrong.

Key words: spatial information modeling, semantic modeling, semantic localization, global discrete grid system

CLC Number:

P208

WANG Dali, TONG Xiaochong, MENG Li, LEI Yi, GUO Congzhou, ZHANG Youwei. Structural modeling of spatial information in texts and semantic localization[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(8): 1398-1410.

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