A Natural Language User Demand Semantic Model for Remote Sensing Image Retrieval

被引:0
作者
Zhang, Xia [1 ]
Chen, Liuyuan [2 ]
Zhu, Xinyan [2 ]
机构
[1] Wuhan Univ, Printing & Packaging Sch, Wuhan, Peoples R China
[2] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Peoples R China
来源
INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS, PTS 1-4 | 2013年 / 241-244卷
基金
美国国家科学基金会;
关键词
Natural Language; User Demand; Remote Sensing Image; Semantic;
D O I
10.4028/www.scientific.net/AMM.241-244.2897
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Remote sensing (RS) image can be applied in many domains. Most research work on RS image retrieval is to meet the demand of professional user. However, there are demands for RS image that comes from non-professional users who propose the requests in natural language (NL) not filling in professional request forms. Some problems are needed to be solved to implement RS image retrieval based on NL user demand. The objective of this research was to propose a user demand semantic model to solve the problem of translation from NL user demand to value requirements. Based on plenty of materials investigated in application domains, the syntax and semantics of NL user demand was analyzed. Semantic relationship is summarized in terms of the semantic analysis. After that, a user demand semantic model is proposed and built with ontology. It can be concluded that the proposed semantic model may help to RS image retrieval based on NL user demand.
引用
收藏
页码:2897 / +
页数:2
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