• DocumentCode
    2715587
  • Title

    Research on the Natural Language Querying for Remote Sensing Databases

  • Author

    Xuan, Xuan ; Jianbo, Liu ; Jin, Yang

  • Author_Institution
    Center for Earth Obs. & Digital Earth, Grad. Univ. of Chinese Acad. of Sci., Beijing, China
  • fYear
    2012
  • fDate
    11-13 Aug. 2012
  • Firstpage
    228
  • Lastpage
    231
  • Abstract
    Natural language querying for remote sensing databases means that the users describe the query object directly in natural language when they query remote sensing (RS) databases. This method is not limited by the options on the query interface, and allows non-professional users to access to the databases easily. After making a study on the status of natural language querying for databases, the paper sums up three methods used in natural query language processing, which are Pattern Matching, Dependency Extraction and Knowledge Extension. Then it proposes a new method for Natural Language Processing (NLP) based on the features of the RS query text, which establishes a prototype system that contains three main steps-keywords extraction, keywords extension and SQL generation. The system implements the conversion from natural query language to database manipulation language (e.g. SQL), which greatly facilitates the users´ query.
  • Keywords
    SQL; knowledge acquisition; natural language processing; pattern matching; query processing; remote sensing; text analysis; NLP method; RS databases; RS query text; SQL generation; database manipulation language; dependency extraction; keywords extension; keywords extraction; knowledge extension; natural language querying; natural query language processing; pattern matching; query object; remote sensing databases; Database languages; Databases; Earth; Knowledge based systems; Natural languages; Remote sensing; Semantics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Service System (CSSS), 2012 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-0721-5
  • Type

    conf

  • DOI
    10.1109/CSSS.2012.65
  • Filename
    6394304