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

Abstract:

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 conclude that the proposed semantic model may help to RS image retrieval based on NL user demand.

• Periodical: Applied Mechanics and Materials (Volumes 241-244)
• Pages: 2897-2900
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.241-244.2897
• Online since: December 2012
• Authors: Xia Zhang, Liu Yuan Chen, Xin Yan Zhu
• Keywords: Natural Language, Remote Sensing Image, Semantic, User Demand

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