IGSNRR OpenIR  > 研究生部
Extracting spatial relations from document for geographic information retrieval
Yuan, Yecheng(袁烨城)
Source PublicationProceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 ; 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 ; Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 ; 2011 19th International Conference on Geoinformatics, Geoinformatics 2011
2011
Source PublicationProceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 ; 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 ; Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 ; 2011 19th International Conference on Geoinformatics, Geoinformatics 2011
Corresponding AuthorYuan, Yecheng(袁烨城)
Conference DateJune 24, 2011 - June 26, 2011
Conference PlaceShanghai, China
Publication Place445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
PublisherIEEE Computer Society
Funding OrganizationIEEE 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.
AbstractGeographic 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.
KeywordDebris Geographic Information Systems Graph Theory Natural Language Processing Systems Plant Extracts Support Vector Machines User Interfaces Vector Spaces
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/21950
Collection研究生部
Corresponding AuthorYuan, Yecheng(袁烨城)
Recommended Citation
GB/T 7714
Yuan, Yecheng. Extracting spatial relations from document for geographic information retrieval[C]. 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States:IEEE Computer Society,2011.
Files in This Item: Download All
File Name/Size DocType Version Access License
袁烨城(EI).pdf(268KB) 开放获取LicenseView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yuan, Yecheng(袁烨城)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yuan, Yecheng(袁烨城)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yuan, Yecheng(袁烨城)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 袁烨城(EI).pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.