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
Link To Document