Conceptually categorizing geographic features from text based on latent semantic analysis and ontologies. Issue 2 (2nd April 2016)

• Record Type: Journal Article
• Authors: Huang, Yuxia
• Is Part Of: Annals of GIS. Volume 22:Issue 2(2016)
• Page Start: 113
• Page End: 127
• Publication Date: 2016-04-02
• Subjects: Text classification -- ontology -- geographic features -- latent semantic analysis; Geographic information systems -- Periodicals; Periodicals; 910.285
• DOI: 10.1080/19475683.2016.1144648
• Languages: English
• ISSNs: 1947-5683

Abstract

ABSTRACT: Categorizing geographic features from text is a process of assigning a collection of text documents that describe geographic features to predefined categories. This paper presents a new approach to categorize geographic features from text that begins at the level of the individual document. Using latent semantic analysis, similar geographic features are grouped into predefined categories through capturing the semantic context of text. By incorporating ontologies into latent semantic analysis, the domain knowledge can be incorporated into the categorizing process. The proposed approach can allocate each geographic feature into more than one category and is able to identify a set of key concepts to represent each category. The results from an experimental evaluation using the proposed approach showed promise in categorizing geographic features from text.