Syntactic Pattern Recognition of Geospatial Relations Described in Natural Language

被引：0

作者：

Zhu, Shaonan ^{[1
]}

Zhang, Xueying ^{[1
]}

Zhang, Chunju ^{[1
]}

机构：

[1] Nanjing Normal Univ, Key Lab Virtual Geog Environm, MOE, Nanjing, Jiangsu, Peoples R China

来源：

2011 INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND MULTIMEDIA COMMUNICATION | 2011年

关键词：

spatial relations; sequence alignment; syntactic pattern recognition;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Spatial language is one of the basic issues in geographical information science. Natural language is considered as the important resource of geospatial information including geospatial relations. Syntactic patterns represent linguistic characteristics of spatial relations described in natural language, which can be effectively used in spatial information retrieval, spatial query in GIS, cartographic language and spatial information retrieval. The previous research focused on induction syntactic patterns of spatial relations manually. In this paper, a machine learning approach is proposed, which is based on a annotation corpus marked by spatial relations. Firstly, the examples of the spatial relations in the corpus are extracted; secondly, sequence alignment algorithm is used to calculate the similarity between examples of spatial relations; finally, the examples with higher similarity are generalized to generate the syntactic patterns of geospatial relations.

引用

页码：352 / 355

页数：4

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