• DocumentCode
    2057357
  • Title

    A Latent Semantic Analysis-Based Approach to Geographic Feature Categorization from Text

  • Author

    Huang, Yuxia

  • Author_Institution
    Dept. of Comput. Sci., Texas A&M Univ. - Corpus Christi, Corpus Christi, TX, USA
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    87
  • Lastpage
    94
  • Abstract
    Geographic feature categorization from text addresses the need for querying and finding geographic features from text documents. Although many text classification techniques have been developed, there are limitations to apply to geographic features due to the uniqueness of the geography features. In this paper we propose a method to classify geographic features based on latent semantic analysis and domain knowledge. The empirical experiment indicates that the proposed method achieves satisfactory categorizing effectiveness.
  • Keywords
    geography; information retrieval; text analysis; domain knowledge; geographic feature categorization; latent semantic analysis-based approach; text classification techniques; text documents; Ecosystems; Feature extraction; Matrix decomposition; Ontologies; Semantics; Vegetation; Vegetation mapping; Geographic feature; categorization; latent semantic analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing (ICSC), 2011 Fifth IEEE International Conference on
  • Conference_Location
    Palo Alto, CA
  • Print_ISBN
    978-1-4577-1648-5
  • Electronic_ISBN
    978-0-7695-4492-2
  • Type

    conf

  • DOI
    10.1109/ICSC.2011.15
  • Filename
    6061331