Title :
A Latent Semantic Analysis-Based Approach to Geographic Feature Categorization from Text
Author_Institution :
Dept. of Comput. Sci., Texas A&M Univ. - Corpus Christi, Corpus Christi, TX, USA
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;
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
DOI :
10.1109/ICSC.2011.15