Extracting spatial relations from document for geographic information retrieval

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	Extracting spatial relations from document for geographic information retrieval
	Yuan, Yecheng(袁烨城)
	2011
会议名称	2011 19th International Conference on Geoinformatics, Geoinformatics 2011
会议日期	June 24, 2011 - June 26, 2011
会议地点	Shanghai, China
关键词	Debris Geographic information systems Graph theory Natural language processing systems Plant extracts Support vector machines User interfaces Vector spaces
通讯作者	Yuan, Yecheng(袁烨城)
英文摘要	Geographic information retrieval (GIR) is developed to retrieve geographical information from unstructured text (commonly web documents). Previous researches focus on applying traditional information retrieval (IR) techniques to GIR, such as ranking geographic relevance by vector space model (VSM). In many cases, these keyword-based methods can not support spatial query very well. For example, searching documents on "debris flow took place in Hunan last year", the documents selected in this way may only contain the words "debris flow" and "Hunan" rather than refer to "debris" flow actually occurred in "Hunan". Lack of spatial relations between thematic activates (debris flow) and geographic entities (Hunan) is the key reason for this problem. In this paper, we present a kernel-based approach and apply it in support vector machine (SVM) to extract spatial relations from free text for further GIS service and spatial reasoning. First, we analyze the characters of spatial relation expressions in natural language and there are two types of spatial relations: topology and direction. Both of them are used to qualitatively describe the relative positions of spatial objects to each other. Then we explore the use of dependency tree (a dependency tree represents the grammatical dependencies in a sentence and it can be generated by syntax parser) to identify these spatial relations. We observe that the features required to find a relationship between two spatial named entities in the same sentence is typically captured by the shortest path between the two entities in the dependency tree. Therefore, we construct a shortest path dependency kernel for SVM to complete the task. The experiment results show that our dependency tree kernel achieves significant improvement than previous method.
收录类别	EI
会议主办者	IEEE Geoscience and Remote Sensing Society (IEEE GRSS); East China Norm. Univ., Sch. Resour. Environ. Sci.; Shanghai Urban Dev. Inf. Res. Cent.; The Geographical Society of Shanghai; East China Univ. Sci. Technol., Bus. Sch.
会议录	Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011
会议录出版者	IEEE Computer Society
会议录出版地	445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
语种	英语
ISBN号	9781612848488
内容类型	会议论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/21950]
专题	地理科学与资源研究所_研究生部
推荐引用方式 GB/T 7714	Yuan, Yecheng. Extracting spatial relations from document for geographic information retrieval[C]. 见:2011 19th International Conference on Geoinformatics, Geoinformatics 2011. Shanghai, China. June 24, 2011 - June 26, 2011.